+91 98726 60544 hello@mitstech.co Mon–Sat · 09:00–18:30 IST

IT Services in Bengaluru — Cloud, Cybersecurity, AI, Data Analytics and Custom Software Development

What we do

From cloud migrations to 24/7 security operations, we cover the full technology stack - software, AI, cloud, security and data - delivered by one dedicated partner.

AI & Intelligent Automation

AI & Intelligent Automation

From generative-AI copilots and RAG chatbots to predictive models and MLOps, we build production-grade AI on your own data - with governance and security baked in.

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Software Development

Software Development

Custom web, mobile, and enterprise applications engineered with modern, clean architecture - built to scale, easy to maintain, and shipped fast with battle-tested CI/CD pipelines.

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Cloud Solutions & Migration

Cloud Solutions & Migration

We move your infrastructure to the cloud with zero-downtime migrations, cloud-native architectures, and ongoing cost optimization - built to scale as you grow across AWS, Azure, and Google Cloud.

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Cybersecurity & Compliance

Cybersecurity & Compliance

Proactive threat detection, penetration testing, and audit-ready compliance for SOC 2, HIPAA, and GDPR. We harden every layer so your data and your reputation stay protected.

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Data Analytics & BI

Data Analytics & BI

Turn raw data into confident decisions with real-time dashboards, clean data pipelines, and reporting tailored to the way your business actually works.

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Compose your engagement

Pick what you need. See how we'd run it.

Select any combination below and your engagement blueprint builds itself.

Now powered by AI

AI Solutions that deliver

Not hype - production-grade AI built on your own data, with governance, security, and measurable ROI from day one.

Generative AI & Copilots

Custom LLM assistants and RAG chatbots grounded in your own data and docs.

Predictive Analytics

ML models that forecast demand, churn, and risk before it happens.

Intelligent Automation

Automate document, support, and back-office workflows end to end.

AI-Powered Security

Anomaly detection and threat triage that monitors your stack 24/7.

MLOps & Integration

Production pipelines to deploy, version, and monitor models reliably.

AI Strategy

Pragmatic roadmaps that put AI to work on measurable business outcomes.

Explore AI services

What we deliver

01

AI & Automation

Generative AI, predictive models, and intelligent automation built on your data.

Talk to us about this

How we work

A simple, transparent process that ships value early and keeps you in control at every step.

1

Discover

We start by understanding your goals, systems, and constraints - no cookie-cutter proposals.

2

Design

We architect the solution and a phased plan you can actually execute, with clear milestones.

3

Deploy

We implement in thin, reversible slices - shipping value early and de-risking every step.

4

Support

We monitor, optimize, and support 24/7, staying accountable long after go-live.

5

Measure

We baseline before launch and report against it after, so the value is evidenced rather than asserted.

6

Improve

Each quarter we review what the numbers say and agree the next increment worth building.

Industries we serve

A decade of delivering secure, reliable technology across the sectors where uptime and compliance aren't optional.

Fintech & Banking

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Fintech & Banking

Secure, compliant platforms for payments, lending, and core banking.

Healthcare

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Healthcare

HIPAA-ready systems that keep patient data private and always available.

Retail & E-commerce

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Retail & E-commerce

Scalable storefronts and analytics that stay fast through peak demand.

SaaS & Technology

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SaaS & Technology

Cloud-native architecture and DevOps for product teams shipping fast.

Manufacturing & IoT

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Manufacturing & IoT

Connected operations, edge data, and reliable industrial infrastructure.

Public Sector & Education

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Public Sector & Education

Dependable, accessible IT for institutions that serve people at scale.

Services

Fifteen practices. One accountable engineering partner.

Most engagements draw on three or four of these at once — a platform build needs architecture, cloud, QA and security working as one team, not four vendors with four contracts. Each practice below states the problems it solves, what is in the box, and the outcomes we hold ourselves to.

Service 01

Custom Software Development

Systems built around your workflow, not around a licence agreement.

Off-the-shelf software solves the eighty per cent of your business that looks like everyone else's. The remaining twenty per cent — the part that actually differentiates you — is where custom engineering pays for itself. We build the systems that encode how your organisation really works: the approval chain nobody can explain to a vendor, the pricing logic that lives in three spreadsheets, the operational workflow that four departments have quietly built around.

Every build starts with a discovery sprint that maps the real process, not the documented one, and ends with a system your own team can operate and extend. We ship in thin, reversible slices behind feature flags, so business value lands in weeks rather than quarters, and every increment is production-grade — tested, instrumented, and documented — rather than a demo waiting to be rewritten.

Business problems solved

  • Critical processes running on spreadsheets, email threads and institutional memory
  • Licensed products that force expensive process changes to fit their assumptions
  • Legacy applications nobody dares to modify, with no tests and no original authors
  • Integration gaps that are silently bridged by manual re-keying of the same data

Key capabilities

  • Product discovery, domain modelling and technical due diligence
  • Greenfield builds and legacy modernisation with strangler-fig migration
  • Domain-driven design with clean, testable service boundaries
  • Feature-flagged, trunk-based continuous delivery
  • Automated unit, integration, contract and end-to-end test suites
  • Living architecture decision records and runbook documentation

What you receive

  • Product and technical discovery report with a costed delivery roadmap
  • Production application, source code and full IP transfer
  • CI/CD pipelines, infrastructure-as-code and environment parity
  • Automated test suite with documented coverage thresholds
  • Architecture decision records, API reference and operational runbooks
  • Two structured handover sessions plus 30 days of hypercare

Expected outcomes

  • First production slice live in 4–6 weeks, not 4–6 months
  • 60–80% reduction in manual handling for the automated workflow
  • Change lead time measured in hours rather than release windows
  • A codebase your own engineers can own without a rewrite

Technologies we use

  • TypeScript
  • React / Next.js
  • Node.js
  • Python / FastAPI
  • Java Spring Boot
  • .NET 8
  • Go
  • PostgreSQL
  • Redis
  • Docker

Ideal for: Mid-market and enterprise teams whose competitive edge depends on a process no vendor product models correctly — and who need it engineered once, properly.

Scope a custom build

Service 02

Enterprise Web Applications

High-traffic, role-aware web platforms that hold up under audit.

Enterprise web applications fail in predictable ways: permissions that were bolted on late, reporting that brings the database to its knees at month-end, and a front end that degrades the moment a real dataset arrives. We design for those failure modes first — role-based access as a first-class model, read paths separated from write paths, and performance budgets enforced in CI rather than discovered in production.

The result is a platform that behaves the same for ten users and ten thousand: predictable latency, complete audit trails, granular permissions that map to your org chart, and an interface that senior staff can actually use without a training course. We build to WCAG 2.2 AA from the first commit, because retrofitting accessibility into a mature enterprise application is one of the most expensive corrections there is.

Business problems solved

  • Internal portals so slow that staff maintain shadow spreadsheets instead
  • Permission models that cannot express real organisational hierarchy
  • Month-end reporting that degrades performance for every other user
  • Audit requests that take days of manual log reconstruction to answer

Key capabilities

  • Multi-role, attribute-based access control with delegated administration
  • Server-side rendering and streaming for fast, indexable first paint
  • Complex workflow, approval-chain and state-machine engines
  • Reporting and export pipelines isolated from transactional load
  • Immutable audit logging on every state transition
  • WCAG 2.2 AA accessibility and full keyboard operability

What you receive

  • Interaction design system and component library
  • Role and permission matrix mapped to your organisation
  • Production web platform with SSO and directory integration
  • Performance budget report and load-test evidence
  • Accessibility conformance report (VPAT-ready)
  • Administrator and end-user documentation

Expected outcomes

  • Sub-second p95 interaction latency at production data volumes
  • Single sign-on across the estate, eliminating credential sprawl
  • Audit evidence produced in minutes instead of days
  • Measurable reduction in shadow-IT spreadsheet workarounds

Technologies we use

  • Next.js
  • Astro
  • React
  • TypeScript
  • Spring Boot
  • .NET
  • PostgreSQL
  • Elasticsearch
  • Redis
  • Keycloak / Entra ID

Ideal for: Organisations replacing an ageing internal portal, intranet or line-of-business system that hundreds of employees depend on daily.

Review your platform

Service 03

Mobile App Development

Native-quality iOS and Android, shipped from one disciplined codebase.

Most enterprise mobile projects are not really about mobile — they are about giving field staff, customers or partners a reliable interface to systems that were designed for a desk. That means the hard problems are offline behaviour, sync conflict resolution, background processing, device security and release governance, not pixel placement. We treat those as the core of the engagement.

We build cross-platform with React Native or Flutter where the economics favour a shared codebase, and go fully native with Swift or Kotlin where the product depends on platform capability. Either way you get store-ready releases, crash-free session rates above 99.5%, over-the-air update capability for JavaScript layers, and a mobile release train your team can operate independently.

Business problems solved

  • Field teams re-entering data into a laptop hours after the job is finished
  • Apps that break the moment connectivity drops in a warehouse or basement
  • Separate iOS and Android codebases drifting apart feature by feature
  • App store rejections and release cycles that block business commitments

Key capabilities

  • Offline-first architecture with conflict-aware synchronisation
  • Biometric authentication, secure storage and certificate pinning
  • Push notification, deep-linking and in-app messaging infrastructure
  • Background sync, geolocation and device-hardware integration
  • Automated store submission with staged rollout and instant rollback
  • Crash, performance and adoption analytics wired in from day one

What you receive

  • Platform strategy note: cross-platform versus native, with cost modelling
  • Published iOS and Android builds under your developer accounts
  • Offline sync specification and conflict-resolution rules
  • Automated build, signing and release pipeline
  • Store listing assets, privacy manifests and data-safety declarations
  • Mobile analytics dashboard and crash-monitoring setup

Expected outcomes

  • 99.5%+ crash-free sessions across both platforms
  • Full functionality retained through connectivity loss
  • Release cadence reduced from quarterly to fortnightly
  • One codebase covering both stores where it is economically right

Technologies we use

  • React Native
  • Flutter
  • Swift / SwiftUI
  • Kotlin / Jetpack Compose
  • Firebase
  • SQLite / WatermelonDB
  • Fastlane
  • App Center
  • Sentry
  • GraphQL

Ideal for: Companies with field operations, a customer-facing service, or a partner network that needs dependable mobile access to core systems.

Plan your mobile build

Service 04

SaaS Product Engineering

From first tenant to enterprise-ready platform, without the rebuild.

Building a SaaS product is a different discipline from building software. Tenancy, metering, entitlement, self-service onboarding, subscription lifecycle and per-tenant data isolation all have to be decided early, because retrofitting them is the single most common cause of a full platform rewrite two years in. We make those decisions deliberately, document the trade-offs, and build the platform primitives before the feature backlog buries them.

We work with founders taking a first product to market and with established firms productising an internal system into a revenue line. Either way, the engagement covers the commercial machinery — plans, trials, usage metering, dunning, upgrade paths — alongside the product itself, so the business model is executable rather than aspirational.

Business problems solved

  • A promising product that cannot support its first enterprise buyer's security review
  • Tenant data separated by a WHERE clause and a hope
  • Manual onboarding that makes every new customer a services project
  • No usage metering, so pricing changes are guesswork

Key capabilities

  • Multi-tenant architecture: pooled, bridged or siloed, chosen deliberately
  • Self-service signup, trial, onboarding and provisioning flows
  • Subscription billing, usage metering and entitlement enforcement
  • Tenant-level configuration, branding and feature flagging
  • Enterprise readiness: SSO/SAML, SCIM provisioning, audit export
  • Product analytics, activation funnels and churn instrumentation

What you receive

  • Tenancy and isolation design document with a security rationale
  • Production multi-tenant platform with provisioning automation
  • Billing and entitlement integration with reconciliation reporting
  • Enterprise readiness pack: SSO, SCIM, audit trail, data residency notes
  • Product analytics instrumentation and activation dashboard
  • Scale and cost model projected to 10× current tenant count

Expected outcomes

  • Onboarding time cut from days of manual setup to self-service minutes
  • Per-tenant unit economics visible and controllable
  • Enterprise security questionnaires answered from existing evidence
  • Platform headroom for 10× growth without re-architecture

Technologies we use

  • Next.js
  • NestJS
  • PostgreSQL (RLS)
  • Stripe
  • Temporal
  • Kafka
  • Auth0 / WorkOS
  • Kubernetes
  • Terraform
  • PostHog

Ideal for: SaaS founders past product-market fit, and enterprises turning a proven internal tool into a commercial product.

Talk SaaS architecture

Service 05

UI/UX Design & Design Systems

Research-led interfaces and a design system that survives the roadmap.

Enterprise software is rarely abandoned because it lacks features. It is abandoned because using it is slower than the workaround. Our design practice starts with contextual research — watching the people who will actually use the system do their current job — and turns that into interfaces that reduce steps, surface the right information, and make errors hard to commit and easy to recover from.

We deliver a design system, not a set of screens: tokens, components, states, motion rules and accessibility annotations, shipped as a coded library your engineers consume directly. That closes the usual gap where a beautiful prototype degrades in implementation, and gives every future feature a consistent starting point.

Business problems solved

  • Users routing around the official system with spreadsheets and chat
  • Every new feature designed from scratch, so nothing feels like one product
  • High training cost and long ramp time for new staff
  • Accessibility gaps discovered during procurement, not during design

Key capabilities

  • Contextual enquiry, stakeholder interviews and task analysis
  • Journey mapping, service blueprints and information architecture
  • Interactive prototypes validated with real users before code
  • Design tokens and a coded component library with full state coverage
  • WCAG 2.2 AA annotation: focus order, labels, contrast, motion
  • Usability testing, analytics review and iteration cycles

What you receive

  • Research findings with prioritised, evidence-backed opportunities
  • End-to-end journey maps and information architecture
  • High-fidelity prototypes covering primary and edge-case flows
  • Coded design system published to Storybook with usage guidance
  • Accessibility annotation pack and conformance checklist
  • Usability test report with a measured before/after baseline

Expected outcomes

  • 30–50% fewer steps to complete the primary task
  • Support tickets tied to confusion measurably reduced
  • New-feature design time cut by reusing the system
  • Accessibility conformance evidenced before procurement asks

Technologies we use

  • Figma
  • Storybook
  • Design tokens (W3C DTCG)
  • Tailwind CSS
  • Radix UI
  • Framer Motion
  • Maze
  • Hotjar
  • Axe DevTools
  • React Aria

Ideal for: Teams whose product is functionally complete but operationally painful, and organisations standardising design across multiple applications.

Book a UX review

Service 06

Cloud & DevOps Engineering

Migrations that do not wake anyone up, and platforms teams enjoy running.

A cloud migration that lifts and shifts a monolith onto larger instances moves your bottleneck to a bigger invoice. We re-architect where it pays — managed data services, autoscaling, event-driven decomposition — and leave alone what genuinely does not need to change, because discipline about scope is what keeps a migration on schedule.

Beyond migration, we build the platform layer: infrastructure as code, golden CI/CD paths, environment parity, progressive delivery and cost governance. The goal is a platform your engineers can operate without a specialist on speed dial, with the guardrails that stop a Friday deployment becoming a Saturday incident.

Business problems solved

  • Cloud spend rising every quarter with no owner able to explain the delta
  • Deployments that require a change window and a nervous senior engineer
  • Snowflake environments where staging never predicts production
  • Scaling handled by over-provisioning because autoscaling was never tuned

Key capabilities

  • Cloud strategy, landing-zone design and well-architected review
  • Zero-downtime migration with reversible, per-service cutovers
  • Infrastructure as code, GitOps and immutable environments
  • Kubernetes, serverless and container platform engineering
  • Progressive delivery: canary, blue-green and automated rollback
  • FinOps: tagging, showback, rightsizing and commitment planning

What you receive

  • Migration assessment: workload inventory, dependencies and wave plan
  • Landing zone with account, network and identity guardrails
  • Complete infrastructure-as-code repository, reviewed and documented
  • Golden CI/CD pipeline templates adopted across services
  • Rollback runbooks tested before every cutover wave
  • FinOps baseline with a 12-month cost trajectory and savings plan

Expected outcomes

  • Zero customer-facing downtime across migration waves
  • 25–40% infrastructure cost reduction within two quarters
  • Deployment frequency up an order of magnitude; change failure rate down
  • Mean time to recovery measured in minutes, not hours

Technologies we use

  • AWS
  • Microsoft Azure
  • Google Cloud
  • Kubernetes
  • Terraform
  • Argo CD
  • GitHub Actions
  • Helm
  • Istio
  • Prometheus

Ideal for: Organisations modernising off on-premise or co-located infrastructure, and teams whose cloud bill has outgrown their cloud maturity.

Request a cloud assessment

Service 07

API & System Integration

One coherent nervous system across the tools you already bought.

Most enterprises do not have a software problem; they have a seams problem. The ERP does not talk to the CRM, the warehouse system exports a nightly CSV, and a person in operations is the integration layer. We replace that with designed, contract-first interfaces — real APIs, real events, real error handling — so data moves once, correctly, and everyone reads the same numbers.

We design for the reality of integration: partners who change payloads without notice, systems that go down mid-transaction, and duplicate messages that must not create duplicate orders. That means idempotency, retries with backoff, dead-letter handling and reconciliation reporting as standard, not as a phase two that never arrives.

Business problems solved

  • The same customer record maintained separately in four systems
  • Nightly batch files that silently fail and are noticed a day later
  • Point-to-point integrations forming a web nobody can safely change
  • Partner onboarding that takes months of bespoke engineering each time

Key capabilities

  • Contract-first API design with OpenAPI and AsyncAPI specifications
  • REST, GraphQL, gRPC and webhook interface engineering
  • Event-driven integration with brokers and an outbox pattern
  • iPaaS and ESB implementation, or a pragmatic replacement of one
  • Idempotency, retry, dead-letter and reconciliation design
  • API gateway, rate limiting, versioning and developer portal

What you receive

  • Integration landscape map with data-ownership decisions per entity
  • Published API contracts with versioning and deprecation policy
  • Integration services with monitoring, alerting and replay capability
  • Reconciliation reports proving both sides agree
  • Developer portal and partner onboarding guide
  • Runbooks for every failure mode we designed against

Expected outcomes

  • Manual re-keying between core systems eliminated
  • Integration incidents detected automatically rather than reported by users
  • Partner onboarding reduced from months to days
  • A single, agreed system of record per business entity

Technologies we use

  • Kong / Apigee
  • Apache Kafka
  • RabbitMQ
  • MuleSoft
  • Azure Service Bus
  • GraphQL Federation
  • OpenAPI
  • Temporal
  • Debezium
  • n8n

Ideal for: Organisations running several best-of-breed platforms that were never designed to work together, and anyone whose data quality problem is really an integration problem.

Map your integrations

Service 08

AI/ML & Generative AI

Production AI grounded in your data, governed from day one.

The gap between an impressive AI demo and a system people trust with real work is mostly engineering: retrieval quality, evaluation harnesses, guardrails, fallback behaviour, cost control and monitoring. We build the second thing. Every engagement starts with a data-readiness audit and a ground-truth evaluation set, because without a way to measure correctness you cannot tell improvement from change.

We build copilots, retrieval-augmented assistants, document-processing pipelines, forecasting models and agentic automations — always with an explicit answer to four governance questions: what data can this system see, who sees its output, what happens when it is confidently wrong, and how does a human override it.

Business problems solved

  • Pilots that impress in a demo and fail on real documents
  • Assistants that invent plausible answers with no way to detect it
  • Knowledge locked in thousands of PDFs nobody has time to read
  • Unbounded model spend with no per-feature cost attribution

Key capabilities

  • AI readiness audit: lineage, label quality, freshness, governance, volume
  • RAG systems with semantic chunking, hybrid search and re-ranking
  • Domain copilots and agentic workflows with tool use and human approval
  • Intelligent document processing: extraction, classification, validation
  • Forecasting, classification and anomaly-detection models
  • MLOps: versioning, evaluation harness, drift detection, cost telemetry

What you receive

  • AI readiness report with go / no-go recommendation per use case
  • Ground-truth evaluation set and a published accuracy baseline
  • Production AI service with guardrails and graceful degradation
  • Governance sheet per system: data access, oversight, override, escalation
  • Cost telemetry dashboard with per-feature attribution
  • Model and prompt versioning with a documented rollback path

Expected outcomes

  • Measured accuracy against a real evaluation set, not vibes
  • 40–70% reduction in manual effort on the targeted workflow
  • Answer traceability: every response cites its source
  • Predictable per-request cost with alerting on drift

Technologies we use

  • Claude (Anthropic)
  • Azure OpenAI
  • Amazon Bedrock
  • Vertex AI
  • LangGraph
  • pgvector
  • Pinecone
  • MLflow
  • PyTorch
  • Ray

Ideal for: Organisations with a specific, measurable process worth automating — and the appetite to measure whether it actually worked.

Start with a readiness audit

Service 09

Data Engineering & Analytics

One version of the truth, arriving fast enough to act on.

Most reporting disputes are not disagreements about strategy; they are two teams computing the same metric two different ways. We fix that at the source: modelled, tested, documented pipelines feeding a warehouse where each metric has exactly one definition, one owner and one lineage trail back to the system that produced it.

On top of that foundation we build the analytics people actually use — operational dashboards for the teams doing the work, executive views for the people setting direction, and embedded analytics inside your own product where your customers benefit from it. Every pipeline ships with data quality tests that fail loudly before a bad number reaches a board deck.

Business problems solved

  • Three departments reporting three different revenue figures
  • Analysts spending most of their week preparing data rather than analysing it
  • Dashboards nobody trusts, so decisions wait for a manual extract
  • No lineage, so a wrong number takes days to trace to its source

Key capabilities

  • Modern data stack: ingestion, warehouse, transformation, semantic layer
  • Batch and streaming pipelines with change-data-capture
  • Dimensional and data-vault modelling with a governed metric layer
  • Automated data quality testing, freshness SLAs and lineage tracking
  • Self-serve BI, executive dashboards and embedded product analytics
  • Data governance: cataloguing, classification and access control

What you receive

  • Source-system audit and prioritised data architecture blueprint
  • Production pipelines with orchestration, alerting and backfill capability
  • Governed semantic layer: one definition per metric, with an owner
  • Data quality test suite and freshness SLA dashboard
  • Executive, operational and self-serve BI dashboards
  • Data dictionary, catalogue and analyst enablement sessions

Expected outcomes

  • Reporting cycle cut from days to near-real-time
  • Metric disputes resolved by definition rather than by meeting
  • Analyst time reallocated from data prep to analysis
  • Pipeline cost reduced via incremental processing and storage tuning

Technologies we use

  • Snowflake
  • Databricks
  • BigQuery
  • dbt
  • Apache Airflow
  • Kafka / Debezium
  • Apache Spark
  • Power BI
  • Looker
  • Great Expectations

Ideal for: Organisations whose data volume has outgrown spreadsheets and whose leadership wants decisions grounded in numbers everyone agrees on.

Assess your data platform

Service 10

ERP & CRM Solutions

Implementations, extensions and integrations that fit how you sell and operate.

ERP and CRM programmes fail on process, not technology. The platform arrives configured to a reference model that resembles your business generically and contradicts it specifically, and the organisation quietly reverts to its old habits with an expensive licence attached. We start with process design, decide explicitly what to standardise and what to preserve, and configure from that decision.

We implement, extend and integrate across the major platforms, and we build the custom modules that sit alongside them where the standard product genuinely does not fit. Data migration is treated as a first-class workstream with reconciliation evidence, because a go-live with untrusted data is a go-live nobody adopts.

Business problems solved

  • A costly platform in place while the real work still happens in spreadsheets
  • Customisations so deep that upgrades have become impossible
  • Sales, finance and operations working from incompatible customer records
  • A migration whose opening balances nobody is willing to sign off

Key capabilities

  • Process design and fit-gap analysis before any configuration
  • Implementation and configuration across major ERP and CRM platforms
  • Custom modules and extensions built to survive vendor upgrades
  • Data migration with cleansing, mapping and reconciliation evidence
  • Bidirectional integration with finance, commerce and support systems
  • Role-based training, adoption tracking and hypercare

What you receive

  • Fit-gap analysis with an explicit standardise-versus-preserve decision log
  • Configured environment with documented settings and rationale
  • Migration plan, executed load, and signed-off reconciliation report
  • Integration layer connecting the platform to the wider estate
  • Role-based training material and administrator handbook
  • Adoption dashboard tracked through the first two quarters

Expected outcomes

  • Order-to-cash and quote-to-cash cycle time measurably reduced
  • One customer record shared by sales, finance and operations
  • Upgrade path preserved — extensions survive platform releases
  • Adoption measured, not assumed

Technologies we use

  • Salesforce
  • Microsoft Dynamics 365
  • SAP S/4HANA
  • Odoo
  • NetSuite
  • HubSpot
  • Zoho
  • Power Platform
  • MuleSoft
  • Azure Logic Apps

Ideal for: Growing organisations outgrowing disconnected tools, and enterprises rescuing an implementation that has stalled short of adoption.

Discuss your ERP or CRM

Service 11

QA & Test Automation

Confidence to ship on a Friday, backed by evidence.

Slow releases are usually a testing problem wearing a process costume. When the only way to gain confidence is a two-week manual regression pass, releases batch up, batches get risky, and risk becomes a change advisory board. We invert that: a fast, layered automated suite that gives a trustworthy answer in minutes, so releasing becomes routine.

We build the pyramid deliberately — many fast unit tests, a solid layer of integration and contract tests, and a small, ruthlessly maintained set of end-to-end journeys. We also fix the thing that quietly destroys trust in automation: flakiness. A suite people ignore is worse than no suite at all.

Business problems solved

  • Regression cycles that add weeks to every release
  • A test suite so flaky that red builds are routinely ignored
  • Defects found in production that a contract test would have caught
  • No performance or accessibility gate until a customer complains

Key capabilities

  • Test strategy and risk-based coverage design
  • Unit, integration, contract and end-to-end automation
  • Cross-browser and real-device mobile test execution
  • Performance, load and soak testing with enforced budgets
  • Automated accessibility and visual regression checks in CI
  • Flake detection, quarantine and remediation discipline

What you receive

  • Test strategy mapped to business risk, agreed with stakeholders
  • Automated suite integrated into CI with clear pass/fail gates
  • Performance baseline and enforced regression budgets
  • Accessibility and visual regression gates
  • Quality dashboard: coverage, flake rate, escaped defects
  • Enablement so your team maintains the suite after handover

Expected outcomes

  • Regression feedback in under 15 minutes instead of weeks
  • Escaped-defect rate reduced by more than half
  • Release cadence increased without increasing change failure rate
  • Flake rate held under 1%, so red builds mean something

Technologies we use

  • Playwright
  • Cypress
  • Jest / Vitest
  • PyTest
  • JUnit
  • Pact
  • k6
  • BrowserStack
  • Axe-core
  • Allure

Ideal for: Teams whose release confidence depends on manual effort, and platforms where a production defect carries real financial or regulatory cost.

Get a quality assessment

Service 12

Cybersecurity Services

Defence in depth, evidenced for auditors and tested by attackers.

Security work divides into two halves that need each other: hardening the estate so attacks fail, and producing the evidence that proves it to auditors, insurers and enterprise buyers. We do both. Identity, network, application and data layers are hardened in that order, because identity is where almost every breach we are called in after actually began.

We then stand up detection and response so incidents are contained rather than discovered, run penetration tests against the result, and package the evidence for SOC 2, ISO 27001, HIPAA or GDPR readiness. Security awareness training closes the loop on the vector no control fully covers.

Business problems solved

  • Permissions accumulated over a decade that nobody has ever reviewed
  • Enterprise deals stalling on a security questionnaire
  • No detection capability — you would learn of a breach from a third party
  • Compliance evidence assembled by hand under audit pressure

Key capabilities

  • Security posture assessment and threat modelling
  • Identity hardening, MFA rollout and least-privilege access review
  • Zero Trust architecture and network segmentation
  • Penetration testing, red teaming and secure code review
  • SIEM, detection engineering and incident response retainer
  • SOC 2, ISO 27001, HIPAA and GDPR readiness programmes

What you receive

  • Prioritised risk register with owners and remediation timelines
  • Penetration test report with retest evidence on every finding
  • Hardened identity and network baseline, documented
  • Detection rules, alert runbooks and an incident response plan
  • Compliance evidence pack mapped control-by-control
  • Security awareness programme with phishing simulation results

Expected outcomes

  • Critical and high findings closed and independently retested
  • Audit passed on the first attempt, with evidence produced on demand
  • Mean time to detect reduced from months to minutes
  • Security questionnaires answered from a maintained evidence library

Technologies we use

  • Microsoft Defender
  • CrowdStrike
  • Wazuh
  • HashiCorp Vault
  • Okta / Entra ID
  • Snyk
  • Burp Suite
  • Cloudflare Zero Trust
  • Trivy
  • Vanta / Drata

Ideal for: Regulated businesses, enterprise vendors facing customer security review, and any organisation whose exposure has outgrown its controls.

Request a security review

Service 13

IT Consulting & Advisory

Independent judgement on the decisions that are expensive to reverse.

Some decisions deserve an outside view precisely because they are hard to undo: build versus buy, platform selection, whether an ageing system can be modernised or must be replaced, and whether the technology organisation is shaped for where the business is heading. We give a direct answer with the reasoning shown, not a deck of options that leaves the decision exactly where it started.

Our advisory work is deliberately independent of implementation revenue. We will tell you to buy the product, keep the incumbent, or do nothing this year when that is the right call — and we have. Recommendations come costed, sequenced and tied to the business outcome that justifies them.

Business problems solved

  • A platform decision with a seven-figure consequence and no in-house precedent
  • Technical debt that everyone acknowledges and nobody can quantify
  • A roadmap driven by vendor timelines rather than business priorities
  • Due diligence on an acquisition target's technology and team

Key capabilities

  • Technology strategy and multi-year roadmap development
  • Architecture review and technical debt quantification
  • Build-versus-buy analysis and vendor selection support
  • Technical due diligence for investment and acquisition
  • IT operating model, team structure and capability planning
  • Interim CTO and architecture leadership

What you receive

  • Current-state assessment with evidence and stakeholder input
  • Target architecture and a sequenced, costed transition plan
  • Build-versus-buy recommendation with total cost of ownership modelling
  • Technical debt register quantified in delivery-velocity terms
  • Operating model and capability plan
  • Board-ready summary in business language

Expected outcomes

  • A decision made with defensible reasoning, not vendor influence
  • Roadmap sequenced by business value and dependency reality
  • Technical debt made visible, prioritised and budgeted
  • Leadership and board aligned on the same plan

Technologies we use

  • TOGAF
  • C4 model
  • Wardley mapping
  • AWS/Azure Well-Architected
  • DORA metrics
  • SAFe / Scrum
  • ITIL 4
  • FinOps Framework
  • NIST CSF
  • ISO 27001

Ideal for: Boards, CTOs and investors facing a consequential technology decision that needs an independent, experienced second opinion.

Book an advisory session

Service 14

Digital Transformation

Sequenced modernisation that ships value every quarter.

Transformation programmes fail when they are structured as a single, multi-year bet that must complete to be worth anything. Leadership changes, budgets shift, and the programme is cancelled with nothing in production. We structure transformation as a sequence of independently valuable increments, each of which leaves the organisation measurably better off even if the next one never happens.

That means picking a first domain that matters enough to be real but is small enough to finish, proving the pattern end-to-end, and then scaling it with the operating-model changes — team topology, funding model, governance — that make the pattern repeatable rather than heroic.

Business problems solved

  • A transformation programme two years in with nothing live
  • Digital initiatives that stall at pilot and never reach production
  • Core processes still paper-based while the website looks modern
  • Change fatigue from previous programmes that promised and did not deliver

Key capabilities

  • Value-stream mapping and opportunity prioritisation
  • Legacy modernisation via strangler-fig, domain by domain
  • Process automation and straight-through processing
  • Customer and employee experience redesign
  • Operating model, team topology and funding model change
  • Benefits realisation tracking against a signed baseline

What you receive

  • Value-stream map with quantified friction and opportunity sizing
  • Transformation roadmap sequenced into independently valuable increments
  • Reference implementation of the first domain, in production
  • Operating model and team topology recommendations
  • Benefits baseline and quarterly realisation reporting
  • Internal enablement so the pattern scales without us

Expected outcomes

  • Measurable business value in production within the first quarter
  • Cycle time on the transformed process cut by half or more
  • A repeatable modernisation pattern your teams can apply themselves
  • Benefits evidenced against baseline, quarter by quarter

Technologies we use

  • Kubernetes
  • Kafka
  • Camunda
  • Power Automate
  • Temporal
  • Terraform
  • Snowflake
  • Salesforce
  • Azure Integration Services
  • Backstage

Ideal for: Established organisations carrying legacy systems and process debt that need modernisation without betting the year on a single release.

Plan your transformation

Service 15

Application Maintenance & Support

Someone accountable at 2am, and the improvements that mean fewer 2am calls.

Software does not finish at go-live. Dependencies age, certificates expire, traffic patterns shift, and the people who built it move on. Our managed support covers the whole surface: 24/7 monitoring and incident response, security patching, dependency currency, performance tuning and a continuous backlog of small improvements that stop debt compounding.

Every engagement has a named service delivery manager, published SLAs, and a monthly service review with real numbers — incidents by cause, SLA attainment, error budget consumed and what we changed to reduce recurrence. Support that only reacts is a cost line; support that reduces incident volume quarter over quarter is an investment.

Business problems solved

  • The one engineer who understands the system has left
  • Dependencies years behind, with known vulnerabilities and no upgrade path
  • Incidents reported by customers before monitoring notices
  • The same root cause producing an incident every few weeks

Key capabilities

  • 24/7 monitoring, alerting and on-call incident response
  • Tiered SLAs with response and resolution commitments by severity
  • Security patching and dependency currency management
  • Proactive performance tuning and capacity planning
  • Blameless post-incident reviews with tracked corrective actions
  • Continuous small-enhancement backlog inside the retainer

What you receive

  • Service transition and knowledge capture, including runbooks
  • Monitoring, alerting and escalation configuration
  • Published SLA matrix and escalation path
  • Monthly service report: incidents, SLA attainment, root causes
  • Quarterly technical health review and roadmap
  • Disaster recovery test evidence on an agreed cadence

Expected outcomes

  • 99.9% availability against a published SLA
  • 15-minute response on critical incidents, around the clock
  • Incident volume trending down quarter over quarter
  • Dependency and patch currency maintained continuously

Technologies we use

  • Datadog
  • Grafana
  • Prometheus
  • Sentry
  • PagerDuty
  • OpenTelemetry
  • Jira Service Management
  • Dependabot
  • Snyk
  • Statuspage

Ideal for: Organisations running business-critical applications without a full in-house platform team, and teams inheriting a system they did not build.

Compare support tiers
Delivery methodology

Six phases. Every one of them produces something you can hold.

A methodology is only worth publishing if it commits us to something. Each phase below names its activities, the artefacts you receive, and the one outcome that has to be true before we move on.

  1. PHASE 01 1–3 weeks

    Discover

    01

    We learn the business before we propose the system — talking to the people who perform the process, not only the people who describe it.

    Activities

    • Stakeholder interviews across business, operations and technology
    • Contextual observation of the current process as actually performed
    • System, data and integration landscape audit
    • Constraint mapping: regulatory, commercial, contractual and calendar
    • Success criteria defined as measurable business outcomes

    Artefacts you receive

    • Discovery report with evidence
    • Current-state process and system map
    • Prioritised opportunity backlog
    • Risk register with owners

    Output: An agreed problem statement and success metric that business and engineering both signed, before a line of code is scoped.

  2. PHASE 02 2–4 weeks

    Design

    02

    Architecture, experience and delivery plan designed together, so the technical decision and the user outcome are never optimised in isolation.

    Activities

    • Target architecture with explicit, documented trade-offs
    • Domain modelling and service boundary definition
    • Interaction design and prototypes validated with real users
    • Threat modelling and compliance control mapping
    • Delivery plan sequenced into independently valuable slices

    Artefacts you receive

    • Architecture decision records (C4 diagrams)
    • Interactive prototype
    • API contracts (OpenAPI / AsyncAPI)
    • Costed, sequenced delivery roadmap

    Output: A design your team can challenge on the merits, with the reasoning behind every consequential decision written down.

  3. PHASE 03 6–20 weeks

    Build

    03

    Two-week sprints producing a working, deployable increment every time — behind feature flags, with tests and instrumentation included, never deferred.

    Activities

    • Trunk-based development with mandatory peer review
    • Test-first engineering across unit, integration and contract layers
    • Continuous integration with automated quality and security gates
    • Sprint demos with the stakeholders who set the success criteria
    • Continuous architecture review against the agreed design

    Artefacts you receive

    • Working software in a production-like environment
    • Automated test suite with coverage reporting
    • Sprint demo recordings and decision log
    • Living technical documentation

    Output: Software in an environment you can use, every two weeks — so course corrections happen while they are still cheap.

  4. PHASE 04 2–4 weeks

    Assure

    04

    Independent verification before anything reaches customers: performance under real load, security under real attack, accessibility under real assistive technology.

    Activities

    • Load, stress and soak testing against agreed performance budgets
    • Penetration testing and dependency vulnerability review
    • Accessibility audit against WCAG 2.2 AA with assistive technology
    • User acceptance testing with the teams who will operate the system
    • Disaster recovery rehearsal and rollback verification

    Artefacts you receive

    • Performance test report with headroom analysis
    • Penetration test report plus retest evidence
    • Accessibility conformance report
    • Signed UAT acceptance record

    Output: Evidence — not assurances — that the system holds under the conditions that actually matter.

  5. PHASE 05 1–2 weeks

    Launch

    05

    Progressive rollout with a rehearsed rollback. Nobody on our team has ever been asked to make a two-in-the-morning judgement call we had not already planned for.

    Activities

    • Cutover runbook rehearsed end to end in a staging environment
    • Canary release with automated health-based promotion
    • Data migration with reconciliation sign-off before switchover
    • Hypercare with engineering on standby and heightened monitoring
    • Operational handover, training and runbook walkthrough

    Artefacts you receive

    • Cutover and rollback runbooks
    • Migration reconciliation report
    • Go-live decision record with named approvers
    • Operations handbook and training materials

    Output: A launch that is uneventful by design, with a tested route back at every step.

  6. PHASE 06 Ongoing

    Evolve

    06

    The system keeps improving after launch: monitored, patched, tuned and extended against a benefits baseline agreed before we started.

    Activities

    • 24/7 monitoring, alerting and incident response
    • Security patching and dependency currency management
    • Performance tuning and capacity planning against real traffic
    • Continuous enhancement backlog prioritised with your team
    • Quarterly technical health and benefits realisation review

    Artefacts you receive

    • Monthly service report with SLA attainment
    • Blameless post-incident reviews with tracked actions
    • Quarterly technical health review
    • Benefits realisation report against baseline

    Output: Declining incident volume, maintained currency, and business benefit evidenced quarter after quarter.

Engagement models

Five ways to work with us — including the ones that suit us least.

The commercial model should fit the shape of the work, not our revenue recognition. Each option below states what it is bad at as plainly as what it is good at, because that is the half that actually helps you choose.

Pricing philosophy

How we estimate — and why we won't quote before we understand.

We do not publish a price list, because a number produced before discovery is either padded against unknowns or optimistic enough to require a difficult conversation later. Here is exactly how we get to a figure you can take to finance.

What moves the number

  • Scope & complexity

    Number of distinct capabilities, integration count, data migration volume and the regulatory obligations that apply.

  • Team shape

    Seniority mix and squad size needed to hold both the quality bar and the timeline you actually need.

  • Timeline pressure

    Compressed delivery costs more because it means parallel workstreams and a larger coordination overhead — we will always show you the cheaper, slower option too.

  • Integration surface

    The systems we must interoperate with, and how well documented, stable and reachable they are in a test environment.

  • Assurance depth

    Penetration testing, accessibility audit, load testing and compliance evidence scale with the risk the system carries.

  • Run commitment

    SLA tier, hours of cover and disaster recovery objectives for the operational period after launch.

How we get there

  1. 01

    Free consultation

    A 30-minute call to understand the problem and tell you honestly whether we are the right partner for it.

  2. 02

    Paid discovery

    One to three weeks, fixed price, producing an architecture, a plan and an estimate. The output is yours whether or not you continue with us.

  3. 03

    Costed proposal

    A phased plan with a cost range per phase, the assumptions each range depends on, and what would move it.

  4. 04

    Commercial model

    Fixed scope, dedicated team, time and material or managed delivery — chosen to fit the work rather than our revenue recognition.

  • No change fee for clarifying something we should have asked during discovery
  • Rate cards published by seniority — no unexplained blended rates
  • Estimate ranges shown with their assumptions, never a single false-precision number
  • Full IP, source code and infrastructure definitions transfer to you on every engagement
How we compare

The four options on your shortlist, described honestly.

We are not the right answer for every project. A skilled freelancer is better value for a well-defined, short piece of work, and a global systems integrator has scale we do not. Here is where each option genuinely wins.

Comparison of Mits against freelancers, small agencies and large generic vendors across ten evaluation criteria.
Criterion Mits Freelancers Small agency Large generic vendor
Senior engineering on your project Always — the architect who designs it reviews the code Depends entirely on the individual Often, but spread thin across clients Senior in the pitch, junior on delivery
Architecture & documentation ADRs, C4 diagrams and runbooks as standard Rarely produced Variable, often informal Extensive, though not always current
Security & compliance ISO 27001 aligned; SOC 2, HIPAA, GDPR readiness in scope Ad hoc Basic practices, limited evidence Strong — with cost and process to match
Continuity risk Squad model with documented handover High — a single point of failure Moderate — small bench Low, but with constant staff rotation
Speed to first production value 4–6 weeks Fast to start, slow to production-grade 6–10 weeks 3–6 months after contracting
Cost profile Mid — priced on outcomes Lowest hourly, highest rework risk Low to mid Highest, with change-order exposure
IP & source ownership Full transfer, every engagement Usually yours, rarely documented Usually yours Often licensed back to you
Post-launch support 24/7 tiers with published SLAs Best-effort, subject to availability Business hours 24/7, at enterprise pricing
Scaling the team Add a squad in 2–3 weeks Not possible Limited by bench size Fast, though onboarding cost is yours
Accountability when it goes wrong Named delivery lead, one hop to a decision None contractually meaningful Direct, but with limited recovery capacity Contractual, via an account management chain

Table scrolls horizontally on narrow screens. Characterisations reflect patterns we see repeatedly in competitive engagements, not any specific competitor.

Managed support

Support that reduces incidents, not just responds to them.

Every tier includes a named service delivery manager, a published SLA and a monthly review with real numbers — incidents by root cause, SLA attainment, and what we changed to stop the same thing happening again.

How an incident actually runs

  1. 1

    Detect

    Synthetic checks, SLO-based alerting and anomaly detection surface issues before users report them.

  2. 2

    Triage

    Severity assigned against a published matrix; P1 pages the on-call engineer and opens a bridge within the SLA.

  3. 3

    Resolve

    Engineer with system context leads; communications go out on a fixed cadence until service is restored.

  4. 4

    Review

    Blameless post-incident review within five working days, with corrective actions tracked to closure in the backlog.

Not sure where to start? Book a free 30-minute technology assessment.

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