Assistants grounded in your data
Retrieval pipelines over your documents, tickets and databases, so answers cite a real source instead of improvising one.
- Cited answers
- Private by default
- Sub-second retrieval
AI Engineering Studio
Generative AI, built into the software your business already runs.
We design and ship AI features that hold up in production — assistants grounded in your own data, agents that complete real work, and the evaluation and cost controls that keep them dependable.
Currently deployed acrosscustomer support
- 6+
- Years shipping software
- 40+
- Products delivered
- 12
- Countries served
assistant.ts
// Grounded answer over the customer's own data
const answer = await assistant.ask({
query: "Which invoices are overdue?",
retriever: vectorStore,
guardrails: { citations: true },
});Answer cites 3 source documents
Response in 840ms
Cost capped at ₹0.12 / query
Tools and models we build with
OpenAIAnthropic ClaudeLlamaLangChainPineconepgvectorHugging FacePyTorchNext.jsTypeScriptGoKubernetesOpenAIAnthropic ClaudeLlamaLangChainPineconepgvectorHugging FacePyTorchNext.jsTypeScriptGoKubernetes
Generative AI
AI that does a job, not a demo.
Most AI projects stall between a convincing prototype and something a business can depend on. We build for the second half — grounding, evaluation, guardrails and cost control included from the start.
Agents that complete real work
Multi-step agents that call your internal APIs to move a task to done, pausing for human approval at the steps that carry risk.
- Tool calling
- Approval gates
- Full audit trail
Document and data intelligence
Contracts, invoices and forms turned into structured records with confidence scores, replacing manual entry rather than adding review work.
- Structured output
- Confidence scoring
- Human review queue
AI inside existing software
We integrate into the product you already ship — your stack, your auth, your data model — rather than asking your users to adopt another tool.
- Your stack
- Your auth model
- No rip-and-replace
Evaluation and guardrails
Test suites for model behaviour, regression checks on every prompt change, and guardrails that fail closed when confidence drops.
- Offline evals
- Regression gates
- Fail-closed defaults
Cost and latency engineering
Model routing, caching and context trimming that hold response times and per-user cost inside a budget you set in advance.
- Model routing
- Response caching
- Spend ceilings
How we engage
Four steps from question to production.
Short, checkable stages. You see working software against your own data before the large commitment, not after.
- 01
Discovery
We map the workflow, the data that already exists, and where a model genuinely beats deterministic code. Some problems should not use AI, and we will say so.
- 02
Prototype
A working slice against your real data inside two to three weeks, measured on accuracy, latency and cost before anything is committed to.
- 03
Production
Hardening into the live product: evaluation suites, guardrails, observability, access control and rollback paths.
- 04
Operate
Ongoing model updates, regression testing and cost tuning as usage grows and the underlying models change underneath you.
Not sure whether your problem needs AI?
That is a reasonable question, and often the answer is no. A short call is usually enough to tell.
Capabilities
What we take on.
An AI layer is only as good as the software underneath it. We build both, which is why the two do not end up fighting each other.
Generative AI Integration
We embed LLMs into the software you already run — assistants that answer from your own documents, drafting and summarisation inside existing workflows, and structured extraction that replaces manual data entry.
- RAG over private knowledge bases
- In-product copilots and assistants
- Document understanding & extraction
- Evaluation harnesses and guardrails
AI Agents & Automation
Agents that carry out multi-step work against your real systems — tool calling into internal APIs, human approval where it matters, and full traces of every action taken.
- Tool-calling agents over internal APIs
- Workflow and back-office automation
- Human-in-the-loop approval gates
- Observability and action audit trails
AI Platform Engineering
The layer that makes AI features safe to operate: model routing and fallback, caching, vector infrastructure, evaluation pipelines, and spend controls that hold under production load.
- Model routing, fallback and caching
- Vector database design and tuning
- Offline evals and regression testing
- Usage metering and spend controls
Product Engineering
Full-stack product work from a blank repository to a released system — the web platforms, APIs and internal tools that the AI layer plugs into.
- Next.js, React and TypeScript
- Node.js and Go service APIs
- Design systems and component libraries
- Performance, SEO and accessibility
Mobile Applications
Cross-platform and native mobile products, including on-device and hybrid AI features where round trips to a server are too slow or too costly.
- React Native and Flutter
- Native iOS and Android
- Offline-first synchronisation
- Release and store operations
Cloud & DevOps
Infrastructure that carries AI workloads predictably — GPU and inference capacity, autoscaling, CI/CD, and the monitoring that catches regressions before customers do.
- AWS, Azure, GCP and DigitalOcean
- Docker and Kubernetes
- CI/CD pipelines and IaC
- Inference capacity and autoscaling
About
A small engineering team, deliberately.
We are a product engineering studio that builds AI-native software and embeds generative AI into the systems companies already run — assistants grounded in private data, agents that complete real work, and the platform engineering that keeps them reliable in production.
Code Crushers has been building software since 2019. The work has shifted: what used to be web and mobile delivery is now mostly getting language models to behave predictably inside products that real businesses depend on.
We stay small on purpose. The engineers who scope your project are the ones who write the code, which removes the layer where requirements usually go missing.
Measured before shipped
Every AI feature gets an evaluation set and a baseline. If a change to a prompt or model degrades accuracy, the test suite catches it before your users do.
Built into what exists
We work inside your stack, your auth and your data model. Fewer new systems to run means fewer places for the work to quietly rot.
Honest about fit
Plenty of problems are better solved with ordinary deterministic code. We will tell you when that is the case, even though it is the smaller engagement.
- 6+
- Years shipping software
- 40+
- Products delivered
- 12
- Countries served
- 2-3 wks
- To a working prototype
Clients
What the people who hired us say.
Code Crushers developed our complete e-commerce platform in just 8 weeks. Their Next.js expertise and attention to detail helped us achieve 300% increase in online sales within 3 months of launch.
The AI-powered inventory management system built by Code Crushers revolutionized our operations. We reduced manual work by 70% and improved accuracy to 99.5%. Excellent technical expertise and support!
Our mobile app for farmers has reached 50,000+ downloads thanks to Code Crushers' React Native development. The offline functionality and regional language support made all the difference.
Working with Code Crushers was seamless. They created our fashion e-commerce website with beautiful UI/UX design and integrated payment gateway. Our conversion rate improved by 45%!
The logistics tracking system developed by Code Crushers helped us optimize our delivery routes and reduce costs by 25%. Real-time tracking and analytics dashboard exceeded our expectations.
Code Crushers built our learning management system that now serves 10,000+ students across India. The video streaming integration and progress tracking features are outstanding!
Contact
Tell us what you are trying to build.
Describe the problem in plain terms — we will come back with whether AI is the right tool for it, a rough shape for the work, and what it would take.
- support@codecrushers.in
- Phone
- +91 9561611828
- Office
- Pune, Maharashtra, India
- Hours
- Mon – Fri, 9:00am – 6:00pm IST
Every enquiry is read and answered by an engineer, not a bot.
Start a project
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