Custom AI App Development for the Enterprise

From HIPAA-compliant RAG knowledge bases to multi-model LLM routing architectures, we engineer production-grade AI applications using FastAPI, LangChain, Pinecone, and the latest GPT-4o and Claude APIs.

FastAPILangChainLangGraphPineconeGPT-4oClaude 3.5Azure OpenAI
<200ms
API Response Latency
Benchmark at P95 server-side
40-70%
LLM Cost Optimisation
Reduction via intelligent model routing
8-12 Weeks
Time to Production
For enterprise-grade AI applications

Enterprise AI Engineering Services

Every engagement goes beyond prototyping into production-ready, secure, and scalable AI application architecture.

Enterprise AI Backend Engineering

We build the foundational backend for complex AI applications using FastAPI (Python 3.12+) for high-concurrency async processing, combined with Cursor IDE for AI-accelerated development. Our engineers use Claude Code to autonomously write, test, and debug production backend code, cutting development cycles by up to 60%.

  • FastAPI async architecture
  • Cursor & Claude Code accelerated dev
  • REST & WebSocket API design

LangChain & LangGraph Application Layer

For AI applications requiring complex reasoning chains and stateful workflows, we engineer using LangChain and LangGraph. This covers multi-step document analysis tools, AI-powered CRM integrations, intelligent triage systems, and enterprise knowledge management platforms that integrate with your existing ERP and CRM.

  • Multi-step LLM chain engineering
  • Stateful LangGraph workflow apps
  • ERP & CRM agent integrations

RAG Knowledge Application Development

We build Retrieval-Augmented Generation applications that allow your AI to answer questions grounded in your private enterprise data. Using Pinecone Serverless for sub-100ms vector retrieval, FastAPI ingestion pipelines, and OpenAI Embeddings or Cohere Reranker for accuracy, your AI never hallucinates on your data.

  • Pinecone Serverless vector store
  • Cohere Reranker for accuracy
  • Multi-tenant data isolation

Multi-Model AI Application Architecture

Not all tasks suit the same model. We build model routing architectures that select GPT-4o Mini for high-volume classification, Claude 3.5 Sonnet for complex reasoning, and Llama 3.3 70B for on-premise sensitive data. This reduces LLM API costs by 40-70% while maintaining best-in-class quality across user interactions.

  • Intelligent model routing
  • GPT-4o Mini + Claude 3.5 Sonnet
  • 40-70% LLM cost reduction

Regulated Industry AI Applications

Building AI for healthcare, finance, or legal? We develop HIPAA-compliant, SOC 2-ready AI applications with encrypted vector stores, audit logging, PII redaction pipelines, and private LLM deployments using Azure OpenAI Service or AWS Bedrock to ensure your data never leaves your compliance boundary.

  • HIPAA & SOC 2 aligned architecture
  • PII redaction pipelines
  • Azure OpenAI & AWS Bedrock support

AI Analytics & Intelligence Dashboards

We build AI-powered analytics platforms that go beyond static reporting. Using GPT-4o Code Interpreter capabilities, LangChain data analysis agents, and real-time streaming with Server-Sent Events, your dashboards ask questions of your data and surface insights proactively, without the need for a dedicated data analyst.

  • Conversational data analysis
  • GPT-4o Code Interpreter integration
  • Real-time streaming analytics

Skill-Based Agentic Backends

We implements the 2026 SKILL.md standard to build highly modular agentic backends. By packaging complex business logic into portable skill modules, we enable your applications to scale its agent capabilities without increasing context complexity or management overhead.

  • Modular SKILL.md backend logic
  • Portable agent capability packages
  • Scalable reasoning architectures

Built Secure,
Deployed Proven

Every AI application we deliver passes production-readiness gates: security audits, load testing, and MLOps monitoring before it touches your real users.

Uptime SLA
Avg Time to Production

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