Service

Custom AI Development

Production-grade AI systems built for your exact requirements.

Beyond off-the-shelf APIs — we build custom AI systems using fine-tuned models, RAG architectures, and bespoke ML pipelines. When your use case is too specific for a generic solution, we engineer the right one.

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95%+
Task-specific accuracy
60%
Lower cost vs generic APIs
4 wks
Avg. delivery to production

Overview

What we actually build

Most companies don't need to train models from scratch. They need AI systems intelligently assembled from the right components — the right model, grounded with the right data, wrapped in the right architecture. We specialise in RAG (Retrieval-Augmented Generation) pipelines, model fine-tuning, embedding systems, and AI product development that integrates cleanly into your existing stack.

Who this is for

CTOs, product managers, and engineering teams at growth-stage startups and mid-market companies who need AI that's tailored to their data and domain.

RAG Pipeline Development
Custom retrieval-augmented generation systems that ground AI responses in your proprietary data.
Model Fine-Tuning
Fine-tune open-source or proprietary models on your domain data for higher accuracy and lower cost.
LLM Integration & Orchestration
Integrate OpenAI, Anthropic, Gemini, or open-source models with proper prompt engineering and fallback logic.
Vector Database Setup
Pinecone, Weaviate, Chroma, or pgvector — we architect your semantic search and retrieval layer.
Evaluation & Testing
Rigorous evals to measure accuracy, hallucination rate, latency, and cost before production launch.
API & SDK Development
Clean APIs your team can integrate, with proper rate limiting, authentication, and documentation.

Use Cases

What clients use this for

Internal knowledge base Q&A over company documents
Domain-specific document analysis and extraction
AI-powered search across product catalogues or content libraries
Custom code generation or review tools
Automated report generation from structured data
Industry-specific language models for legal, medical, or financial domains

Process

How we deliver it

01
Discovery & Data Audit
We review your data sources, use case requirements, and define success metrics before writing a line of code.
02
Architecture Design
We design the full system — model selection, retrieval strategy, data pipeline, and API surface.
03
Build & Evaluate
Development with continuous evaluation against your defined success metrics throughout.
04
Deploy & Iterate
Production deployment with monitoring, feedback loops, and iterative improvement.

FAQ

Common questions

01
When do I need custom AI vs just using the OpenAI API?
Use the API for generic tasks. Go custom when you need domain-specific accuracy, cost control at scale, data privacy, or proprietary competitive advantage.
02
Do you fine-tune models or just prompt engineer?
Both — we choose based on ROI. Fine-tuning is worth it when accuracy requirements are high and inference volume justifies the upfront cost.
03
What data do we need to provide?
It depends on the system. RAG pipelines need your documents and knowledge base. Fine-tuning needs labelled examples. We'll guide you through data preparation.
04
Who owns the models and code you build?
You do. All IP transfers to you on project completion.

Ready to get started?

Tell us about your project — we'll scope it, answer your questions, and show you exactly how we'd approach it.

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