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Eclipseturns mid-market companies into AI-native ones — designed and run by engineers who've shipped at NASA, Vercel, Shopify, WordPress, and Nielsen. Not a deck. Not a framework. An installation.
Most companies are leaving that on the table because their teams are using AI like a search engine instead of a force multiplier. The gap between "we have Claude licenses" and "our team ships meaningfully faster with AI" is where Eclipse lives.
Every engagement runs the same playbook — audit, deploy, practice, scale. The tier sets the depth, the team size, and how much we customize. Not sure which fits? That's what the call is for.
A focused pilot for small teams ready to move fast. Onsite kickoff, full tooling setup, custom agents tuned to your codebase, and a 30-day forward plan. The fastest way to see what's possible.
Real adoption across a mid-sized engineering org. Audit, deploy, role-specific practice, and measurement — compressed into two weeks of focused work. Includes a mid-engagement demo day where your team shows each other what they've built.
The full installation. Org-wide fluency, custom agents built across departments, internal champions trained to run the protocol after we leave, business outcomes measured and reported to leadership. For companies committed to becoming AI-native.
We embed with your team, read your codebase, and shadow your workflows. You get a current-state map, capability gap analysis per role, and a ranked-opportunity backlog.
The right stack, configured for your stack. Claude Code, Cursor, Cedar, MCP integrations, custom skills built against your conventions, SSO and security handled. By end of this phase, every engineer is shipping production work with AI in the loop.
Role-specific intensives, hands-on builds inside your real codebase, daily office hours, and an internal #ai-wins channel we seed and run. This is where excitement compounds and adoption locks in.
Custom agents embedded into the workflows that matter, measurement harness wired to real business outcomes, internal champions trained to extend the protocol after we leave. You get a forward roadmap and an exec readout.
One-command install into any repo. Pick a specialist, drop it in, get to work. Your engineers get the full library on Day 1 of any tier — and we build custom agents specific to your codebase during the engagement.
Browse all 6 agents →Maps the score before the gig. Reads a codebase end-to-end, then proposes the smallest change that gets you the biggest win.
Treats your codebase like a safe. Threat-models, finds the soft spots, and writes the patches before the postmortem.
Sees what your logs are hiding. Stitches traces, metrics, and incidents into one narrative — then tells you the next move.
The people running your engagement have shipped at scale. We've architected commerce platforms, built AI products in production, and launched apps used by millions. We teach AI fluency because we use it every day to build real things.
AI isn't like a migration — we engineer the moments that make engineers want this. Day 1 wins, custom agents that solve your team's specific complaints, a tiny win-channel that runs itself. Surprising adoption is wins. Top-down adoption is the average of three.
We'll ask about your org, your current AI usage, and what you'd want shipped in your engagement. We'll recommend a tier, scope the work, and send a proposal within a week. If we're not the right fit, we'll tell you who is.