Your AI tools are only as goodas their context.
HILLS Lab helps engineering teams connect Slack, Linear, Jira, GitHub, Sentry, docs, incidents, and production rules into trustworthy context systems for Claude, Cursor, Codex, Copilot, and whatever comes next.
Not another AI wrapper. The context layer around it.
Models will improve and tools will rotate. The durable company asset is a context system that knows what is true, current, relevant, permissioned, and source-backed before any agent acts.
Connect the operating surface
GitHub, Linear, Jira, Slack, Sentry, docs, incidents, and deployment rules each hold part of the truth.
Govern memory and permissions
Agents need read access first, scoped write policies later, and a reviewable trail for every durable memory update.
Measure reliability
Good context should reduce wrong assumptions, wasted file reading, bad PRs, and risky production changes.
Context infrastructure for software teams
Practical audits, workflows, implementation, and evals for teams that want AI coding tools to work with real company context.
AI Context Audit
Know what your agents can safely know
Map the real context surface across Slack, Linear/Jira, GitHub, Sentry, docs, incidents, and production rules. Identify stale docs, missing provenance, dangerous permissions, and workflow gaps.
Agent-Ready Workflow Setup
Read-first access before autonomy
Design the rules, scopes, and context packets that let Claude, Cursor, Codex, and Copilot use the right project context without leaking private information or trusting stale assumptions.
Context System Implementation
Memory with source, freshness, and review
Build durable memory and retrieval around decisions, tickets, PRs, incidents, and runbooks. Every useful memory item needs a source, scope, status, and review path.
Agent Reliability Evals
Prove the context layer works
Run practical evals that compare the same developer tasks with and without the context system: fewer wrong assumptions, less wasted reading, better PRs, and safer incident response.
Audit Your AI Context Layer
Tell us which tools your team uses today. We'll help map the context surface, permissions, stale assumptions, and first reliable agent workflows.
Context Details
Share your workflow and tools
Quick Response Guarantee
We respond to all inquiries within 4 hours.
What Happens Next?
Initial Review
We review your project details and prepare a tailored response.
Strategy Call
30-minute consultation to explore solutions.
Custom Proposal
Detailed project roadmap with timeline, stack, and investment.
Prefer Direct Contact?
Give agents context before autonomy.
The first useful step is not letting an agent change production. It is giving it reliable read access, provenance, permissions, and evals so the team can see where it helps and where it fails.