AI Product Development
From concept to production-ready AI product — engineered end to end.
AI Agent Development for Every Business Need
From single-purpose task agents to enterprise multi-agent systems – built for production, not just demos.
AI Web App Development
Full-stack AI-powered web applications built with React, Node.js, Python, and cloud-native architecture — production-ready, scalable, and engineered around your users’ actual workflows.
- React & Node.js full-stack
- Cloud-native architecture
- Production from day one
AI MVP Development
A working AI product in 6–10 weeks — validated with real users before full investment is committed. From concept and architecture through to a live, testable product your team can ship.
- 6–10 week delivery
- Real-user validation
- Investor-ready build
AI SaaS Platform Development
End-to-end development of AI-powered SaaS products — multi-tenant architecture, subscription and billing infrastructure, and AI features built into the core product, not bolted on after.
- Multi-tenant architecture
- Billing & auth included
- AI-native from the start
AI Feature Integration Into Existing Products
LLM-powered features — chat, search, summarisation, recommendations, and automation — integrated into your existing web app or platform without rebuilding what already works.
- LLM feature integration
- No full rebuild required
- Works with existing stack
AI Agent-Powered Internal Tools
Custom internal tools powered by AI agents — workflow automation, data extraction, reporting dashboards, and approval systems that replace manual processes with autonomous, reliable operations.
- Workflow automation
- Internal process agents
- Reporting & dashboards
AI Product Strategy & Technical Scoping
Not sure what to build or where to start? We run a structured discovery sprint — use-case validation, architecture options, build timeline, and a written scope document before any development commitment.
- Use-case validation
- Architecture options
- Written scope document
Real-World Applications
Built for Clients. Shipped to Production.
From autonomous document processors to intelligent enterprise platforms - here is what we have delivered.
AI Credit Underwriting Platform - Fintech SaaS
An SME lender deployed a six-stage AI agent pipeline - from document ingestion to explainable decisions. Analysts review flagged cases only. Fast decisions, consistent underwriting, and full FCA audit compliance.
View Case Study →Six-Stage Agent Pipeline
Explainable credit decisions
LLM Routing Platform - Cost, Quality & Latency Optimisation
Task-aware routing classifies requests, estimates complexity, and selects optimal models via LiteLLM. All decisions are logged, while a React dashboard provides visibility, control, and continuous A/B optimisation.
View Case Study →Intelligent LLM Routing
Optimised for every request
On-Premise LLM & RAG Platform - Government Enterprise AI
An on-premise LLM on NVIDIA DGX hardware with a secure RAG pipeline over internal data. Staff query in natural language with zero data leakage. Rollout is planned across 11+ departments.
View Case Study →Secure Enterprise RAG
On-premise government AI
From Use Case to Production
No black boxes. No surprises. Working agents in your hands, sprint by sprint.
Product Discovery & Scoping
Step 1
We define what to build and why — use-case validation, user journey mapping, AI feature architecture, and a written scope document with timeline and cost estimate before any development commitment.
Architecture & Technical Design
Step 2
Full-stack architecture specified — frontend, backend, AI integration layer, data model, and infrastructure. LLM selection, API design, and security model defined before the first sprint begins.
Agile Build Sprints
Step 3
Two-week sprints with a working, demonstrable product every fortnight. AI features built and integrated against real data — not mocked endpoints or synthetic test cases.
Testing, Validation & Performance
Step 4
Functional testing, AI output validation, load testing, and edge-case coverage completed before any production release. LLM output parsing, fallback logic, and cost monitoring configured at this stage.
Production Launch & Handover
Step 5
Product deployed to your cloud infrastructure. Full documentation, architecture diagrams, and codebase handover completed. 100% code ownership transferred — no licence fees, no lock-in, no ongoing dependency on Khired.
Contact Us
We typically respond within 24 hours.