C.J. Capobianco - AI Developer | ContraWork by C.J. Capobianco
C.J. Capobianco

C.J. Capobianco

AI Systems Engineer | Voice AI, Agents & Automation

New to Contra

C.J. is ready for their next project!

Followed by Jovan P and GALLERY L

Northborough, USA

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Northborough, USA

Cover image for Factory XYZ, a private multi-agent
Factory XYZ, a private multi-agent software development factory that turns a project objective into coordinated build, review, and validation workflows. I architected the agent orchestration, Runtime-C execution layer, operator console, evidence/artifact flow, access controls, and hosted deployment. The system supports initial builds, iterative refinement, dry runs, live mission control, and structured validation across autonomous coding workers. DELIVERABLES / HIGHLIGHTS Multi-agent software development orchestration Private hosted operator console Runtime-C execution and worker coordination layer Build, review, and validation workflow Initial build, iteration, and dry-run execution modes Live mission control with run status and event visibility Artifact and evidence collection for completed work Access-controlled hosted deployment Reusable architecture for coordinating autonomous coding workers
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Cover image for Tracer AI, a private retrieval
Tracer AI, a private retrieval and asset-intelligence platform that turns large codebases, documents, operational data, and knowledge stores into ranked, explainable AI context. I architected the ingestion, classification, scoring, vector retrieval, graph relationships, review and promotion workflows, plus Runtime-C context bundles. Tracer supports tenant-scoped retrieval with citations and keeps source systems read-only. KEY CAPABILITIES • Source ingestion and warehouse scanning • Content classification and asset scoring • Fingerprinting, tagging, and duplicate detection • Vector retrieval with lexical/entity reranking • Knowledge-graph relationships and dependency mapping • Review, approval, rejection, and golden promotion workflows • Explainable citations and bounded Runtime-C context bundles • Tenant-scoped retrieval and source-system isolation • Read-only operation against source CRM/data systems ARCHITECTURE FLOW Raw Sources → Scan → Classify → Score → Fingerprint → Inspect Content → Tag → Review → Approve / Reject → Vector / Graph / Corpus → Tracer Search → Context / Resource Bundle → Runtime-C
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Cover image for Factory XYZ — Multi-Agent AI Software Development Factory
Factory XYZ — Multi-Agent AI Software Development Factory
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Cover image for PayMe is a business payments
PayMe is a business payments front end designed to give companies one clean workspace for getting paid, managing customers, and keeping the transaction flow simple.
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