Services / AI Agents & LLM Integration
AI assistants, agent workflows and LLM features wired into your product and your data, with clear specs, guardrails and verification so the output can be trusted in production. We treat an AI feature like any other part of the system: defined, tested and monitored.
Finding the tasks where a model saves real time, and being clear about the ones where it shouldn’t be trusted to act alone.
Chat and search features that answer from your documents, records and APIs, with sources shown so people can check the answer.
Multi-step agents that call your tools and APIs with scoped permissions, and hand off to a person when a decision needs one.
Summaries, drafting, classification and extraction built into the screens your users already work in.
Written specs for what the model may and may not do, input and output checks, and test sets that catch regressions before users do.
Model choice, caching and logging so you can see what each feature costs and how often it gets things right.
Our open-source agent skills stop a coding agent from inventing decisions nobody made, and from calling a job done when it isn’t. Decisions get written down first, and the work survives a new session or a new machine. It is the same discipline we bring to AI features in client products.
View on GitHub →We start from what has to change for the business: the problem, the people who will use the software and the systems it must connect to.
Requirements, data model and trade-offs are written down and agreed before building, so nobody has to guess later.
Small releases you can see and test, with security, monitoring and performance built in rather than added at the end.
The same team deploys and supports what it built, with no hand-offs where context gets lost.
We choose the model for the task, its cost and where your data is allowed to go. The integration is built so the model can be changed later without rewriting the feature.
By narrowing what it is asked to do, grounding answers in your own data with sources shown, checking outputs before they reach users, and keeping a person in the loop for decisions that matter.
Yes. Most of our AI work sits inside an existing product or workflow, connected through your current APIs and permissions rather than as a separate tool.
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