AI That Ships.
Not Just Demos.
We build production-grade AI systems for small and medium businesses that are ready to automate, augment, or accelerate. RAG pipelines, agentic workflows, LLM integrations — all designed with eval harnesses so you know when the system degrades before your users do.
AI That Holds
In Production.
Most AI demos look impressive. Most AI in production breaks quietly. A RAG pipeline that returns wrong answers with confidence is worse than no AI at all. An agent that goes off-script in production costs you customers.
We build AI systems the way we build all software — with tests, with monitoring, with eval harnesses that tell you when something has degraded. Not just a working demo, but a system you can trust to run your business processes.
We work with SMBs that are serious about AI — not chasing trends, but solving real problems in their workflows, their customer interactions, and their data.
End to End.
Production Ready.
RAG Pipeline Design & Build
End-to-end retrieval-augmented generation systems. Chunking strategy, embedding model selection, vector store tuning, re-ranking, and an eval harness that tells you when the system degrades.
Agentic Workflow Automation
Multi-step reasoning pipelines with deterministic guardrails — tool use, human-in-the-loop checkpoints, and structured output validation so workflows do not go off-script in production.
LLM Integration
Drop AI into your existing stack without a rewrite. We wire LLM inference into your architecture, handle back-pressure, manage token budgets, and keep your audit trail compliant.
AI Automation Pipelines
No-code and low-code automation pipelines using n8n for businesses that need AI-driven workflows without full custom development. Document processing, email triage, report generation.
Custom AI Chatbots & Assistants
Purpose-built AI assistants for customer support, internal knowledge bases, and sales enablement. Grounded in your data, evaluated against your use cases, deployed with monitoring.
AI Architecture Consulting
Not sure where to start with AI? We audit your current stack, identify the highest-value automation opportunities, and give you a clear roadmap — no vendor bias, no fluff.
How We
Build AI.
We do not start with models. We start with your data, your failure modes, and your definition of success. Only then do we pick the tools.
Every system we build has an eval harness from day one. If we cannot measure it, we do not ship it.
Data & Stack Audit
We map your existing data sources, infrastructure, and failure modes before recommending anything. What data do you have? Where does it live? What does a wrong answer cost you?
System Design & Eval Criteria
Architecture design for the AI system with explicit success criteria. What does good look like? What does degradation look like? We define this before writing a line of code.
Build with Evals From Day One
We build the eval harness alongside the system, not after. Every sprint produces a measurable improvement against the defined criteria. You see exactly how the system is performing at every stage.
Deploy, Monitor & Iterate
Production deployment with structured logging, latency budgets, and monitoring. Eval regressions run on every deploy. You know immediately if a model update breaks something.
What We
Work With.
For SMBs
Ready for AI.
Businesses drowning in manual processes
You have repetitive workflows — document processing, email triage, report generation — that are eating your team’s time and are ready to be automated with AI.
Teams sitting on valuable data
You have internal documents, customer data, or domain knowledge locked away in PDFs, databases, or people’s heads. A well-built RAG system makes it queryable and useful.
Products that want to add AI features
You have a SaaS product or internal tool and you want to add AI capabilities — smart search, auto-summarisation, AI assistants — without breaking what already works.
Teams that tried AI and it did not hold
You built something with ChatGPT or a basic LangChain script and it worked in the demo but fell apart in production. You need it built properly this time.
Work With Us
Your Way.
Project Based
A defined scope, a fixed price. Best for building a specific AI system — a RAG pipeline, an agentic workflow, an LLM integration. You know exactly what you are getting and what it costs.
- Scoping and architecture document upfront
- Fixed price and timeline
- Eval harness included
- Full handoff with documentation
Monthly Retainer
Most PopularOngoing AI engineering support on a monthly basis. Best for teams building AI-driven products that need continuous improvement — new features, model updates, performance tuning, monitoring.
- Dedicated hours each month
- Priority response time
- Covers build, evals, and monitoring
- Monthly planning and review
Advisory Call
A single focused session for teams that need expert input on their AI strategy, architecture decisions, or a review of an existing system. Clear recommendations, no ongoing commitment.
- 60 or 90 minute session
- Written summary after the call
- Architecture and strategy review
- No commitment to continue
Ready to Build AI
That Actually Works?
Tell us what you are trying to automate or build. We will tell you honestly what is possible, what it will cost, and how long it will take.