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Your AI delivery partner

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AI ready

A founder-led team that staffs your build with engineers, AI-assisted squads, or agents on a 24/7 shift.

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Solutions launched
500+

Solutions launched

Engineers
300+

Engineers

Countries served
18

Countries served

Delivering
12 yrs

Delivering

Show me around

Trusted by

Expo GroupAl NahdaSilverlineNovaRetailMeridianBluepeakOrbit LabsKinetix
Three ways to staff it

Humans, humans with AI, or agents that never clock off.

Most partners sell you one delivery model. We let you pick per project — and change your mind at any sprint boundary.

The squad above, allowed to use model assistance for the parts of the job it is genuinely good at — tests, migrations, boilerplate, review passes. You set the policy, and we can prove what was used where.

Coverage
Your working hours, agents pick up the queue overnight
Who does the work
Human writes and reviews, AI drafts
AI policy
Scoped by you, per repository
Working day
8–9 hrs/day + overnight queue

What you get

  • Written AI usage policy, agreed before sprint one
  • Per-repository allow and deny list
  • Provenance log of model-assisted changes
  • No client code or data used for training

Best for

Teams that want the throughput without giving up human judgement on architecture and review.

Talk through this model

Not sure which one? Start human, add agents to the parts of the backlog that suit them, and turn them off again if it does not earn its place. The contract does not lock you into a model.

The night shift

What the agents did while your team was asleep.

An agent fleet runs against your repositories around the clock. Every change arrives as a reviewed pull request — never a direct push — and anything ambiguous stops and waits for a human.

Scoped permissionsHard stop listHuman review before you see itNo training on your code

Overnight queue

22:00 — 09:00
  1. 02:00Dependency upgrade opened, tests greenmerged
  2. 03:40Flaky integration test isolated and fixedreview
  3. 05:15Nightly migration batch 7 of 12 completerunning
  4. 06:50Accessibility fix: 14 unlabelled icon buttonsreview
  5. 08:05Escalated to human squad — schema ambiguityescalated
Or run it yourself

We will build the agent setup for your own team

You do not have to rent the workforce from us. We stand the fleet up inside your accounts, write the policy your security team will sign, and train your engineers to run it — then step back.

Agent platform setup

We stand the fleet up inside your accounts — orchestration, sandboxes, secrets, permissions and spend limits — and hand you the keys.

Guardrails and policy

An AI usage policy your security team will sign: what agents may touch, what they may never touch, and how every change is traced.

Evaluation harness

Before an agent is trusted with a task type, it has to pass a suite built from your own codebase and your own past tickets.

Team enablement

Your engineers learn to run, review and extend the fleet, so the capability stays after we leave.

10×

faster deploys

for a q-commerce platform in the UAE

74%

of claims auto-triaged

for a UK insurance group

6 hrs → 20 min

nightly pipeline

for a retail group across India and the GCC

+21%

enquiry conversion

for a property marketplace in Australia

Selected work

Judge us on what changed.

Every engagement closes with a report. These are the numbers from the last page of it.

All case studies
Team extensionQ-commerce platform · UAE

Four squads, one release train, 10× faster deploys

A grocery delivery platform was shipping monthly and losing ground to faster rivals. We embedded four squads alongside their team and rebuilt the release path around trunk-based development.

deploy frequency
10×deploy frequency
change failure rate
-62%change failure rate
squads embedded
4squads embedded
“Our speed problem was never the engineers. It was everything around them. That is what Codestarn fixed.”
VP Engineering — Q-commerce platform, UAE
  • Next.js
  • Node.js
  • Kubernetes
  • AWS
AI & automationInsurance group · United Kingdom

Claims triage that reads the documents before a human does

Adjusters spent their mornings reading PDFs. We built a document-intelligence pipeline that extracts, classifies and routes claims, with a confidence threshold that escalates anything it is unsure about.

claims auto-triaged
74%claims auto-triaged
saved per claim
18 minsaved per claim
extraction accuracy
99.2%extraction accuracy
  • Python
  • LLM pipeline
  • Azure
  • PostgreSQL
Data engineeringRetail group · India & GCC

A nightly run that stopped being nightly

Reporting landed at 9am if it landed at all. We replaced a chain of scheduled scripts with an incremental warehouse and a tested transformation layer, then handed the whole thing to their analysts.

pipeline runtime
6 hrs → 20 minpipeline runtime
tested models
214tested models
to pay back
1 quarterto pay back
  • dbt
  • Snowflake
  • Airflow
  • Python
Our services

Enhancing creativity, step by step.

Four practices that cover the whole path from idea to a system your team runs every day.

AI & Automation

AI-powered applications and agents that automate work, read your data and hand back decisions — not dashboards.

  • LLM and agent systems on your own data
  • Document intelligence and extraction
  • Process copilots inside existing tools
  • Evaluation harnesses and guardrails
  • Model serving, caching and cost control
  • Human-in-the-loop escalation paths

Data & Analytics

Pipelines and platforms that collect, process and model large datasets so the business decides on evidence.

  • Warehouse design on Snowflake or BigQuery
  • Batch and streaming pipelines
  • Tested transformation layers in dbt
  • Semantic models and self-serve BI
  • Forecasting and anomaly detection
  • Data contracts and quality gates

Digital Transformation

Robotic Process Automation and workflow orchestration that strip manual steps out of the operation.

  • RPA with UiPath and Power Automate
  • Workflow orchestration across systems
  • Legacy modernisation without big-bang rewrites
  • ERP, CRM and payments integration
  • Process mining before automation
  • Change management and team handover

Cloud Offering

Scalable cloud foundations on AWS and Azure — so data and applications stay available, secure and cheap to run.

  • Migration to AWS or Azure, phased
  • Kubernetes, IaC and CI/CD pipelines
  • Observability and on-call runbooks
  • Cost engineering and rightsizing
  • Security baselines and compliance evidence
  • Disaster recovery you have actually tested
Ship log

An ordinary Tuesday, across the client estate.

Agencies show you logos. This is the part that actually tells you whether a team is working — what went to production, and how long it took.

codestarn — releases
  1. 09:12orbit-labs/checkoutdeploy succeeded · 4m 02s · eu-west-1
  2. 10:48meridian/data-platformdbt run 214 models · 0 failures
  3. 11:30silverline/rag-serviceindex rebuilt · 1.2M chunks · p95 340ms
  4. 13:05novaretail/mobilerelease 4.7.0 submitted to App Store
  5. 14:22bluepeak/infrak8s rollout complete · 0 restarts
  6. 16:40expo-group/portallighthouse 98 / 100 / 100 / 100
  7. $

Client names shown with permission; repository paths are illustrative.

Inside Codestarn

Not a brochure — the actual operating picture.

What a partner usually finds out in month three, on the page in front of you.

Working hours, right now

  • UAE--:-- — outside working hours
  • USA--:-- — outside working hours
  • UK--:-- — outside working hours
  • Singapore--:-- — outside working hours
  • Australia--:-- — outside working hours

Squads keep a four-hour overlap with your day. Our own clock runs in Surat, India.

Production deploys

409

last quarter

+38% QoQ

Every one of them behind tests, a security pass and a preview deploy.

32

technologies in rotation

Across 6 disciplines. We pick the boring one unless the problem genuinely asks for otherwise.

5

standing certifications

AWS, Azure and Microsoft — renewed, not framed and forgotten.

18 countries, one delivery model

Same rituals, same release gates, whichever time zone signs the contract.

Response
< 1 day
Overlap
4 hrs+
Retention
94%

The one promise

Your code lives in your repositories and your cloud from day one. If you ever want to walk, you walk with everything.

No vendor lock-in clause, no hostage handover fee.

How the work runs

From a first call to a system you own — scroll through it.

Five phases, no hand-off cliff. Most clients see their first demo before week four.

  1. 01Week 0

    The brief

    A 90-minute call, not a questionnaire. We leave with the constraint that actually matters — a deadline, a cost line, a system nobody wants to touch.

    • Discovery call
    • Constraint map
    • Ballpark and risks
  2. 02Week 1–2

    Shaping

    Flows in Figma, the data model on a whiteboard and a thin slice built for real. You see something running before you commit to the roadmap.

    • Clickable prototype
    • Architecture note
    • Thin vertical slice
  3. 03Week 2–3

    Squad online

    Named engineers, in your Slack, on your board. Vetted profiles within 72 hours of the brief — you interview, you choose, we onboard.

    • Profiles in 72h
    • Your tooling, day one
    • Named, not pooled
  4. 04Week 3+

    Shipping

    Two-week sprints with a demo at the end of each one. Every merge runs tests, a security pass and a preview deploy before it reaches you.

    • Fortnightly demo
    • Automated release gates
    • Friday status note
  5. 05Ongoing

    Handover or hold

    Keep the squad, or take the keys. Either way you get the runbook, the architecture decisions and engineers who answer the phone.

    • Runbook and ADRs
    • SLA-backed support
    • Your repos, always

01 / 05

The honest comparison

Three ways to get the work done. Here is where each one hurts.

We are not the right answer for every team. These are the trade-offs we would want to see before signing anything.

Time to a working team
Profiles in 72 hours, squad in 2–3 weeks
Who you actually get
Named engineers you interviewed, not a pool
Cover when someone leaves
Bench cover in days, context stays with us
Code review and testing
Review, tests and a security pass on every merge
Where the IP lives
Your repositories, your cloud, from day one
Control over AI usage
Written policy, per-repository scope, provenance log
Cover outside your hours
Agent workforce on a 24/7 shift, human-gated
Scaling down
Resize the squad at the sprint boundary
Capabilities

Crafting solutions with technology that works for you.

Artificial Intelligence

Vision, NLP and decision systems in production.

Generative AI

RAG, agents and copilots on your own knowledge base.

AR / VR

Immersive training, product and retail experiences.

Blockchain

Smart contracts, wallets and traceable supply chains.

Microsoft Business Apps

Dynamics 365, Power Platform and SharePoint.

Machine Learning

Forecasting, scoring and recommendation engines.

Metaverse

Spatial commerce and virtual venues built to scale.

Data Analytics

Warehouses, semantic layers and self-serve BI.

Our tech

Find your stack on this page.

Picked for the job rather than the trend. If it is already in your estate, we can work in it rather than argue for a rewrite.

32 technologies · 6 disciplines

Frontend

06

Interfaces that stay fast on a mid-range phone.

  • React
  • Next.js
  • TypeScript
  • Angular
  • Vue.js
  • Tailwind

Backend

06

APIs and services that survive a traffic spike.

  • Node.js
  • Python
  • Java
  • .NET
  • Go
  • GraphQL

Mobile

04

One codebase where it makes sense, native where it does not.

  • React Native
  • Flutter
  • Swift
  • Kotlin

Cloud & DevOps

06

Infrastructure you can rebuild from a repository.

  • AWS
  • Azure
  • Kubernetes
  • Terraform
  • Docker
  • GitHub Actions

Data & AI

06

Pipelines and models that hold up in production.

  • PostgreSQL
  • MongoDB
  • Snowflake
  • dbt
  • Airflow
  • LangGraph

Automation & design

04

The work around the code that decides whether it lands.

  • UiPath
  • Power Automate
  • SharePoint
  • Figma
Client voices

What they said once the project was over.

Collected at the closing retrospective, printed unedited.

“Our speed problem was never the engineers. It was everything around them. That is what Codestarn fixed.”

Karim Haddad

VP Engineering · Q-commerce platform, UAE

“The offshore squad felt like our own team by week three. Sprint demos never slipped, and the reporting was better than our in-house baseline.”

Priya Raman

VP Engineering · Logistics SaaS, Singapore

“They rebuilt our data pipeline and cut the nightly run from six hours to twenty minutes. The cost case paid for itself in one quarter.”

Michael Carter

Head of Data · Retail group, United Kingdom

“They argued with our assumptions, then proved the point with a test instead of an opinion.”

Elena Fischer

Chief Product Officer · Property marketplace, Australia

“Nobody on the outside noticed the migration. That was the entire brief.”

Daniel Okoro

Director of Product · Healthcare provider, United States

“Adding a carrier used to be a project. Now it is a config file and a test run.”

Wei Lin Tan

Chief Technology Officer · Logistics SaaS, Singapore

FAQ

Turning your questions into confidence.

The things clients ask before they sign. If yours is not here, write to us and you will get a straight answer.

Yes. Our agent workforce runs against your repositories around the clock — triage, fixes, tests, dependency upgrades and long migrations. Every change arrives as a pull request that a Codestarn engineer has already reviewed, and anything ambiguous escalates to a human squad instead of being guessed at.

Yes, and we will sign it. The AI policy is yours: off entirely, scoped per repository, or agent-first with human review. It is agreed in writing before sprint one, it can change at any sprint boundary, and every model-assisted change is logged so you can audit what was used where.

That is a service in its own right. We stand the fleet up inside your accounts — orchestration, sandboxes, secrets, permissions and spend limits — write the usage policy your security team will sign, build an evaluation harness from your own codebase, train your engineers to run it, and then step back.

No. We run on zero-retention endpoints, and your repositories, tickets and data are never used for training. That commitment goes in the contract alongside the NDA.

Every project runs through code review, automated tests and a security pass before release. We follow OWASP guidance, sign NDAs before the first call, keep source in your repositories and can work inside your VPN or cloud account when compliance requires it.

We start from the job the user is doing, not the screen. Flows are prototyped in Figma and tested with real users before a line of production code is written, and we hold every build to accessibility contrast, keyboard and reduced-motion standards.

Over a decade of delivery, 300+ engineers and a model built around your time zone. You get a dedicated team with named people, not a rotating pool, and a single point of contact who is accountable for the roadmap.

Web and mobile application development, custom enterprise software, AI and automation, data engineering and analytics, cloud migration and DevOps, plus staff augmentation and full offshore development centres.

Yes. Support plans cover monitoring, incident response with agreed SLAs, security patching, dependency upgrades and a monthly improvement budget so the product keeps moving after launch.

Two-week sprints with a demo at the end of each one. Day-to-day communication happens in your Slack or Teams, work is tracked in your Jira or Linear, and you get a written status note every Friday.

A focused MVP typically lands in 10–14 weeks; a full product with back office and integrations runs 4–7 months. We quote fixed scope after a paid discovery sprint, or a monthly team rate if the roadmap is still moving.

Let's talk

About your next project

Tell us where you are stuck. You will get a written proposal with scope, timeline and cost within three working days — no obligation attached.

Start a projectinfo@codestarn.com