LLM-powered agents
Autonomous and human-in-the-loop agents for support, ops, sales and internal knowledge work — with proper guardrails, evals and audit trails.
AI Software Development
Custom AI systems that actually ship — and keep working.
A demo that works on stage is not a product. We build production-grade AI systems: evaluated properly, monitored continuously, and engineered to handle the messy reality of real users, real data and real cost constraints.
What we build
Real AI applications, delivered end-to-end.
RAG & knowledge assistants
Retrieval-augmented systems over your internal documents, wikis, CRMs and data warehouses. Accurate, sourced answers — not hallucinations.
Computer vision
OCR, document extraction, quality inspection, object detection, video analytics. Deployed on cloud, edge or on-device where privacy demands it.
Forecasting & prediction
Demand forecasting, churn prediction, lead scoring, dynamic pricing — built on your data, explained clearly to your stakeholders.
Recommendation systems
Product, content and next-best-action recommendations that lift engagement and revenue. A/B tested, tuned to your KPIs.
AI-native SaaS platforms
New products with AI as the core value, not a bolt-on. From founders' idea to first paying customer in weeks, not quarters.
How we engineer AI
The parts most agencies skip.
Getting a demo working is easy. Making an AI system reliable, safe, monitored and cost-controlled is what separates a prototype from a product.
Evaluation harnesses
Every model we ship has a task-specific eval suite. You get quantifiable answers to "is this good enough?" — not vibes.
Guardrails & safety
Prompt injection defence, PII redaction, output filtering, refusal handling, audit logs. Especially critical in regulated sectors.
Cost control
Caching, batching, smaller-model routing, prompt compression. We routinely cut LLM spend by 60–80% versus naïve implementations.
Observability
Latency, cost, quality metrics per request and per model. Full traces for every AI call. You know what's happening in production, at all times.
Continuous improvement
Feedback loops from real usage feed back into evals and retraining. Your AI gets better every week it runs.
Toolkit
Model-agnostic. Vendor-neutral. Future-proof.
We're not tied to any single LLM provider. We recommend the right model for each job, and design so you can swap providers without a rewrite.
Frontier LLMs
OpenAI GPT, Anthropic Claude, Google Gemini — for tasks where quality matters most.
Open-source LLMs
Llama, Mistral, Qwen — self-hosted or via inference providers, for cost, privacy and control.
Fine-tuning & distillation
Task-specific fine-tunes, LoRA adapters, distilled small models. Cheaper, faster, more reliable than one-size-fits-all prompts.
Vector search
pgvector, Pinecone, Weaviate, Qdrant — chosen for your scale, latency budget and existing infrastructure.
Orchestration
LangChain, LlamaIndex, LangGraph, custom lightweight frameworks — whichever gives the clearest, most maintainable result.
Classical ML
Not everything is an LLM. Gradient boosting, transformers, computer-vision models — the right tool for the job.
Ready to build AI that works?
Let's scope your AI project.
A short call to understand what you're trying to achieve. If it's a fit, we'll come back within a week with a proposal, timeline and price.
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