What our students actually built.
Real systems, built by people who started where you are. Every project below is assembled from the repositories and artifacts the builder actually shipped.
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Operational AI crm records written after calls · September 2026
The Conversation Happened. The CRM Needs the Right Record.
An AI Systems Architect at Colaberry built the part of an admissions team's calling platform that writes each finished call into the CRM: the contact's fields, a task for a person, the call in the conversation history, the transcript as a staff note. The review reads the platform's own record of those writes against its jobs, and states where that record keeps its promise and where a completed job wrote nothing.
Built by Colaberry team
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Operational AI reservation intake deterministic pricing and a held or ready quote queue · September 2026
The Request Was Messy. The Price Couldn't Be.
Reservation requests arrived as web forms, forwarded threads and free text. Colaberry's Managing Director, working as its AI Systems Architect, built a queue that extracts trip details, calculates prices through explicit rules and prepares a reply for a person to review. The calculation is repeatable for the same inputs and rate-card version; the final reply still needs checking, because its model-written amount is not validated against that calculation on the queue path. Sunset in September 2026; told here as a retrospective, limits included.
Built by Colaberry team
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Operational AI an outreach workflow with territory identity and feedback controls · September 2026
The Pipeline Needed More Than One Person.
A small sales team needed a repeatable way to work its pipeline. Colaberry's Managing Director, working as its AI Systems Architect, built a daily outreach queue for an executive ground-transportation company: AI-assisted drafts, territory controls on the server and an explicit sending profile on the human-approved send path. The project established those controls at the API level; its browser identity flow remained unfinished when the project was sunset in September 2026. Told here as a retrospective, limits included.
Built by Colaberry team
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Operational AI call scheduling and pacing · September 2026
The Next Call Needs a Time. And a Place in the Queue.
Campaign calls need an eligible time and a place among the other launches waiting. An AI Systems Architect at Colaberry built a shared scheduling grid and checks before launch for an admissions team's calling platform, and the operating review shows what those controls cover and where the callback path still breaks down.
Built by Colaberry team
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Operational AI platform state and execution · September 2026
The Workflow Grew. So Did the Responsibility.
A recap workflow begins with a call and ends with a useful next step. As an admissions team's calling system took on more of that work, the harder question became where unfinished work lives and who moves it forward. An AI Systems Architect at Colaberry built the answer into a Python API and worker platform, with explicit boundaries between process state, execution and the CRM, and the record states where those boundaries still leak.
Built by Colaberry team
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Operational AI lead journey and traceability · September 2026
Every Lead Has a History. Make It Possible to Follow.
Can an operator explain a lead's current state and name its next scheduled action? In an admissions team's calling system, the console in use today, at one reading on 18 Sep 2026, named the same next action in both of its lead views for open leads with pending work, but it splits the rest of the history across three views, keeps the reason for a campaign switch without showing it, and leaves call-level work out of its trace. An AI Systems Architect at Colaberry built the records and views behind that history.
Built by Colaberry team
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Operational AI action gating and shadow testing · September 2026
Test the Action. Before It Reaches a Customer.
A convincing message from an AI model can still be the wrong thing to send. An AI Systems Architect at Colaberry built the shadow paths in an admissions team's calling system, so that the calls, texts, emails and CRM updates it intended were held at the boundary, and the texts, emails and CRM updates it recorded could be read in full before any of them reached a customer.
Built by Colaberry team
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Repository grounded portfolio generation · September 2026
Your Repositories Already Wrote Your Resume
A developer's GitHub history is already proof of what they can do, and almost nobody can read it. This system reads the repositories through a six-phase pipeline and writes the portfolio, deciding the role in code before the language model is allowed an opinion.
Built by Learner
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Governed AI remediation · September 2026
The AI Proposes, A Verified Human Decides
An AI operations platform for SQL Server infrastructure that proposes remediations and cannot apply one. Every write waits for a verified human, and every decision leaves a record that outlives the session that made it.
Built by Learner
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Operational AI call intent routing · September 2026
The Call Ended. The Next Step Didn't Have To.
When an AI voice agent finishes a call with a prospect, someone has to decide what happens next. Kes, who joined Colaberry as an intern and is now an AI Systems Architect, built the rules that read what the caller asked for and schedule, cancel or stop the follow-up, and then bounded them when they retried too much.
Built by Colaberry team
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Operational AI voice call event recovery · September 2026
Recovering the Calls the Workflow Lost
A voice call could finish while the event saying so never arrived. Follow how the builder traced a silent integration failure, recognised that a one-off script was not a system, and designed idempotent replay, operator visibility and scheduled recovery in five days, then found the tests and the measurement still missing.
Built by Colaberry team
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