Stack Innovations
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Stack Innovations
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Not a chatbot bolted on the side — a copilot that lives inside your app, answers from your own data with citations, and fires real, structured actions: create the record, update the status, jump the user to the right screen. Grounded, guard-railed, and shipped to production.
A ledger of named copilots where the line that moved was a question answered or an action taken — deflection, time-to-value, tasks completed without a human in the loop. 6 of 30 shown · ledger updates as copilots scale.
Pick what a user might ask inside the product and watch the copilot respond — streaming a grounded, cited answer and firing a structured action that executes in the mock app on the left. Flip to actions-only to see the work happen without the chatter; turn grounding off and the answer drifts to generic, uncited guesswork.
Every surface where the copilot can help, every action it's allowed to take, the tool that backs it, and the guard that keeps it safe. This is the room we work in: each capability scoped, grounded, and gated — so the copilot is useful without ever being a liability.
Before a single tool is wired, we pin down what users actually want to do inside your product — the top asks, the actions worth automating, and the ones that must stay behind a human. Then we build the eval set: the intents we'll grade every release against.
A copilot that doesn't read your data invents answers. We wire retrieval over the user's own records and docs — tenant-scoped and access-aware — so every answer is grounded in what this user is actually allowed to see, with citations back to the source.
Answers are half the job. We define the copilot's tools as strict, schema-validated functions — create, update, navigate — so the model emits a structured action your product can execute, not free text a human has to interpret and re-type.
The copilot can read freely. Writing is different. Anything side-effectful — sending, deleting, charging — pauses for an explicit human confirm with the proposed change shown in the UI. Reversible actions flow; irreversible ones wait.
Run the frozen intent set every change and score it — intent resolution, action success, grounding, refusal correctness. No "looks good in the demo." A number that moves, or the change doesn't ship.
Live with caching for cost, streaming for feel, and logging on every intent and action. We watch resolution and action-success as usage grows, catch regressions before users do, and keep the copilot useful as your product changes underneath it.
Every session is signal: failed intents sharpen the prompts, missed actions justify new tools, wrong answers tighten the grounding. Ship-and-forget copilots stall as your product moves on without them. Evaluated and tended, intent resolution compounds.
The models, stores, and tools we actually wire together to ground a copilot in your data, let it answer with citations, and let it take structured, gated actions inside your product. No mystery framework — just the kit that makes a copilot trustworthy.
A free copilot audit to start — bring your product, a list of real user intents, and we'll show you what an in-product copilot would answer and which actions it would take, grounded in your own data. A working prototype, not a pitch.
Get a copilot audit →