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Generative AI Development

LLMs, RAG pipelines, AI agents — practical Gen AI built for production.

GPT-4ClaudeLangChainRAGPythonVector DB
Overview

What we deliver

We help product teams integrate Generative AI that actually works in production — not demos that fall apart under real data. From connecting GPT-4, Claude, and Gemini to your product, to building retrieval-augmented generation (RAG) pipelines, autonomous agents, and AI-powered document workflows, we bring the engineering rigour that most Gen AI projects lack. We focus on accuracy, reliability, cost control, and observability — because shipping Gen AI is harder than it looks.

Generative AI Development
What's Included

Key capabilities

LLM Integration

Connect GPT-4, Claude, Gemini, or open-source LLaMA models to your existing product or workflow.

RAG Pipelines

Retrieval-Augmented Generation for accurate, grounded answers over your private data — documents, databases, and knowledge bases.

AI Agents & Automation

Multi-step agents that plan, reason, and take action — web search, code execution, API calls, and more.

Fine-Tuning & Prompt Engineering

Domain-specific model alignment through fine-tuning, RLHF, and systematic prompt engineering.

AI Chatbots & Copilots

Intelligent assistants embedded in your product — customer support, internal knowledge, sales tools.

Document Intelligence

Summarise, extract, classify, and search large document corpora — contracts, reports, emails, PDFs.

Technology

Our technology stack

LLM Providers

OpenAI GPT-4oAnthropic Claude 3.5Google GeminiMeta LLaMAMistral

Frameworks

LangChainLlamaIndexCrewAIAutogenHaystackSemantic Kernel

Vector Databases

PineconeWeaviateQdrantpgvectorChromaDBMilvus

Cloud AI

AWS BedrockAzure OpenAI ServiceGoogle Vertex AI

Observability

LangSmithLangfuseWeights & BiasesPhoenix
Who It's For

Common use cases

  • Customer support AI automation
  • Internal knowledge base assistants
  • Contract and document processing
  • AI-powered search and discovery
  • Sales intelligence and lead scoring
  • Code generation and developer tools

Not sure if this is right for you?

Talk to an engineer first.

We offer a free 30-minute discovery call to understand your problem and tell you honestly whether we're the right fit — no sales pitch.

Book a Discovery Call →
FAQ

Frequently asked questions

How do you prevent hallucinations in production?
Through RAG (grounding answers in verified data), output validation, confidence scoring, and human-in-the-loop fallbacks. We treat hallucination risk as an engineering problem, not a disclaimer.
Which LLM should we use?
It depends on your accuracy, cost, and latency requirements. GPT-4o and Claude 3.5 Sonnet are our go-to choices for complex reasoning. For cost-sensitive, high-volume use cases, we often use smaller fine-tuned models. We run benchmarks against your data before recommending.
How do you handle data privacy with LLMs?
We can route your data through private deployments (Azure OpenAI, AWS Bedrock), on-premise open-source models, or implement anonymisation pipelines before data hits any third-party API.

Ready to get started?

Tell us about your project. We'll respond within one business day with a tailored proposal.

No long-term contracts
Senior engineers only
US · AU · NZ timezone coverage
14-day trial on retainers