AI That Works
in Production.
AI agents, copilots and automations connected to your real tools and data, with the validation, guardrails and monitoring that keep them reliable once real users arrive. Not sure where to start? Find out in two weeks.
Built for Real Work, Proven in Production
Every solution below is running for a real client today. We start from the problem, not the model.
The problem
Prospects wait hours for answers, and your team spends the day switching between tools to book them in.
What we build
An AI agent that answers questions, checks availability and schedules appointments across text, email, chat and phone, with your team in control.
The problem
Users can't find what they need, and AI features you've tried return answers the interface can't use.
What we build
Natural-language search and an in-product copilot with structured, validated output, so nothing malformed reaches the frontend.
The problem
People review recordings, tickets or documents by hand, and the issues that matter get missed.
What we build
AI that analyses and summarises the work automatically and flags only what needs a person's attention.
The 2-Week AI Discovery Sprint
For teams with several AI ideas and no clear first step, or leaders who need evidence before approving an AI budget. Fixed scope, fixed length, and a decision at the end.
- Your data is never used to train AI models
- We can work inside your own cloud
Use-case audit
We review your workflows and data and rank every AI idea by value, feasibility and data readiness.
Working prototype
We build the strongest use case against your real data, so you see what the AI can actually do.
Go or no-go
A clear recommendation with the risks stated plainly and, if it's a go, a scoped plan for the full build.
Reliability Is the Product
Most AI projects stall after the demo. We engineer AI the way we engineer any production system, with the checks that keep it working once real users arrive.
Validated Outputs
Every model response is checked against a defined structure before it reaches your users or your frontend. Malformed answers are caught, not shipped.
Evaluations, Not Vibes
Features are tested against an evaluation set of real cases, so we can measure whether a prompt or model change made things better or worse.
Guardrails
Clear limits on what the AI can say and do, with a person in control of the actions that matter.
Monitoring & Cost Control
Quality, latency and spend are tracked after launch, so the system stays useful and the bill stays predictable.
Your Data Stays Yours
Your data is never used to train models. We choose the model for each task on accuracy, speed, cost and data requirements.
Your Cloud, If You Need It
When security or compliance requires it, we deploy the AI system inside your own cloud account.
Model-Agnostic, Production-Ready
We pick the model for each task on accuracy, speed, cost and data requirements, and build on the cloud, web and mobile stack that runs it in production.
- OpenAI
- Claude
- Gemini
- Llama
- Qwen
- Hugging Face
- Ollama
- LangChain
- LangGraph
- AutoGen
- Nomic
- Qdrant
- Chroma
- Next.js
- React
- Node.js
- Django
- Flutter
- AWS
- Azure
- DynamoDB
- Redis
- Firebase
- GitHub Actions
AI Running for Real Clients
Agents, copilots and automations we've shipped, with the outcomes they delivered.
PropTech Revenue Intelligence Platform
0 → fully shipped SaaS: 6 modules, 60+ features, 500,000+ records synced
Built a multi-integration PropTech SaaS from zero, with a 24x7 multilingual prospect AI agent and a sync layer that unifies AppFolio, Rent Manager and Rentvine data and catches its own failures.
AI-Powered Event Marketplace
Structured AI output enforced: no malformed responses reaching the frontend
An all-in-one event marketplace connecting vendors, planners and customers, where AI search and a vendor copilot had to work reliably in production, not just in demos.
Teams Call Quality AI Analyzer
50% fewer support tickets, with 95% AI flagging accuracy
Every Microsoft Teams call quality complaint meant a support ticket and a manual investigation call. We built an AI monitoring layer that flags real issues before they become tickets.
Questions About AI Projects
What buyers ask before starting an AI project with us. If your question isn't here, reach out. Every message gets a personal reply.
Contact us for moreTwo fixed weeks. In week one we audit your possible AI use cases and rank them by value, feasibility and data readiness. In week two we build a working prototype of the strongest one, then give you a clear go or no-go with the risks stated plainly.
You keep the use-case audit and the prototype, and you've avoided funding a full build that wouldn't have paid off. A clear no-go is a useful result, and we'll tell you if a simpler, non-AI fix is the better answer.
A short list of the processes or product areas where you think AI could help, access to sample data or documents for those areas, and a person on your side who knows the workflow. We handle the rest.
Yes. Our agents call your APIs to check availability, book appointments, update records and follow up. Each agent has clear permissions, logs every action and hands off to your team for decisions that need a person.
We're model-agnostic and choose per task on accuracy, speed, cost and data requirements. We've shipped with OpenAI, Claude, Gemini, Llama, Qwen and open models via Hugging Face and Ollama, and design systems so the model can be swapped without a rebuild.
Every response is validated against a defined structure before it reaches users, and features are tested against an evaluation set of real cases before each change ships. Guardrails keep the AI within its scope, and quality and cost are monitored after launch.
Find out where AI fits in two weeks.
Book a free 30-minute call with the founder. We'll look at your workflows and tell you honestly whether AI is the right answer, and whether a Discovery Sprint is the right first step.