AI development
company
We build AI products that survive real users, not demos that fall apart the week after the pitch. Retrieval that finds the right context, grounding that stops the model inventing answers, and the eval loop that proves it works. A US company with a senior team, building software since 2015.
Talk to experts nowWhat we build
Production AI, not prototypes. The retrieval, grounding, and evaluation layer that decides whether an AI feature ships. We wrote that layer up in public, in a full production teardown of our hybrid RAG on Qdrant.
RAG systems
Retrieval that answers from your data instead of guessing. Semantic and keyword search together, grounded and cited, so the model stops inventing answers.
AI agents
Agents that do real work with tools and guardrails, not chatbots that fall over the moment a task gets complicated.
AI features in your product
Search, summarization, classification, and copilots, with the retrieval and evaluation underneath so they hold up under real traffic.
The production layer
The eval harness, the cost and latency controls, and the observability that turn a convincing demo into a system you can put your name on.
Built and measured on
An AI feature without an eval loop is a guess deployed to users. We build the measurement in.
- Python
- LangGraph
- Qdrant
- pgvector
- Hybrid search and reranking
- OpenAI
- Anthropic
- Provider-agnostic routing
- RAG and grounding
- Eval harness (golden sets, retrieval precision)
- Observability
AI development, answered
What AI has the 2muchcoffee team shipped?
Production retrieval and agent systems. We published a full teardown of our hybrid RAG on Qdrant, including the grounding and evaluation work, and we maintain public multi-agent repositories you can read.
Do you build AI from scratch or add it to an existing product?
Both. This page is about building an AI product. If you have a product already and want to add AI, see our AI integration services.
How do you stop the model from hallucinating?
Grounding and evaluation. We constrain answers to retrieved, cited context and run an evaluation harness with golden sets, so a change that increases hallucination shows up before your users find it.
Which AI models do you use?
OpenAI and Anthropic families behind a provider-agnostic layer, routed by cost and capability, so you are not locked to one vendor.
How do we start an AI project?
Tell us what you are building on a short call. We scope it, agree the model and timeline, and put senior people on it.
Related reading
Recent write-ups from our engineers.
Contact our team
Our team contacts you within 24 business hours
We collect all the key requirements from you
The team of developers prepares estimation
We can sign NDA since we respect the confidentiality of our clients