Building the data and AI systems that federal programs run on.
Melvis Chafac has spent 13+ years standing up data science and AI functions from scratch, architecting the platforms behind them, and getting the governance right — for regulated industries where correctness is not optional.
Riderentz brings that same discipline to federal and public-sector engagements: enterprise data strategy, production GenAI, and analytics programs built to last past the person who built them.
What this practice delivers
Each line below is drawn from work already shipped in production — not a services menu, a description of what's been built before and can be rebuilt for a mission or agency partner.
Enterprise data strategy
Roadmaps, operating models, and platform decisions that connect an organization's data to its actual decisions — built and defended in front of executive and cross-functional stakeholders across five countries.
GenAI & agentic AI in production
RAG systems, multi-step autonomous agents, and LLM evaluation pipelines shipped and running at scale — including a system that replaced a major third-party vendor product and now processes 2 million records nightly.
Data governance & regulatory compliance
Governance strategy, automated audit-ready workflows, and data-quality frameworks built for a FINRA-regulated fintech platform — the same rigor a federal compliance environment requires.
Modern data platform architecture
Databricks, AWS Glue, and Azure pipelines engineered to process hundreds of millions of records, with cluster and cost optimization built in from day one.
MLOps & model governance
End-to-end frameworks for automated evaluation, retraining, and promotion of models to production — containerized, orchestrated, and monitored, not handed off as notebooks.
Standing up new functions
Two AI and data science organizations built from zero — hiring plans, career ladders, operating rhythm, and performance management — not just staffed, but institutionalized.
What sets it apart on a proposal
Builder, not just an advisorActive hands-on development alongside program leadership — code shipped, not just strategy decks.
Regulated-industry track recordGovernance work built for FINRA oversight — a direct analogue for agencies with strict data and audit requirements.
0-to-1 program experienceTwice built an entire function — team, tooling, and process — where none existed before, with measurable business impact.
Global, distributed team leadershipManaged and mentored teams across the US, Canada, India, UK, and China — comfortable coordinating dispersed technical staff.
Institutional groundingU.S. Military Academy at West Point, graduate study in engineering systems at MIT — a background built around discipline and mission orientation.
Documented financial impactWork tied to concrete outcomes: roughly $500K in annual savings and a projected $12M in new revenue from one system alone.
Where this experience maps to federal work
These are the categories of federal and public-sector engagement this background is best suited for — a starting point for matching to specific solicitations, not a fixed offer list.
Analytics function stand-up
Designing and institutionalizing an analytics or data science capability inside an agency — standards, hiring, and operating rhythm — for programs building this from scratch.
Responsible AI / agentic AI pilots
Scoping and delivering GenAI pilots that need to survive contact with production: evaluation frameworks, guardrails, and a path from prototype to sustained operation.
Data governance & QA modernization
Building audit-ready data quality frameworks for agencies under regulatory or oversight pressure — schema validation, error tracking, and reporting agencies can defend.
Legacy-to-cloud data platform migration
Moving agency data infrastructure onto modern cloud platforms without breaking the reporting and compliance obligations already in place.
Model risk & MLOps governance
Bringing structure to how models get evaluated, retrained, and promoted — relevant wherever an agency needs to show its AI systems are monitored, not just deployed.
Data science workforce development
Upskilling existing staff and building career paths for a technical workforce, drawing on direct experience mentoring teams from entry-level through senior contributor.
Recent program leadership
Senior Manager, Data Science
Leading a 20-person global data science organization across five countries; architecting production AI agents and the testing and release infrastructure behind them.
AI Engineering Manager
Built a 13–15 person AI function from the ground up; replaced a major vendor product with an in-house RAG system saving roughly $500K annually.
Data Governance & Quality Lead (Principal Engineer)
Designed the enterprise data governance strategy for a FINRA-regulated fintech platform, including automated audit-ready workflows.
Senior Director, Data Science
Built end-to-end MLOps frameworks and a production NLP system achieving 99% accuracy on critical document classification.
Data science & analytics leadership
Progressive leadership roles delivering ML, forecasting, and NLP systems across engineering, product, and marketing functions.
Education & certifications
For contracting officers & small business specialists
Fields marked pending will be completed once SAM.gov registration is finalized. Confirm current values on SAM.gov before citing this page in a proposal.
Primary NAICS 518210 covers computing infrastructure, data processing, and hosting-related services. Secondary codes span custom programming (541511), computer systems design (541512), other computer-related services (541519), marketing consulting (541613), other scientific & technical consulting (541690), and R&D in physical/engineering sciences (541714). Riderentz self-identifies as a small, women-owned, and minority-owned business; if formal certification (e.g., WOSB, 8(a), MBE) hasn't been completed yet through the SBA or a certifying body, that's worth pursuing separately — self-identification in SAM.gov is not the same as a certified socio-economic status, and certification is usually what unlocks set-aside eligibility on solicitations restricted to those categories.
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For solicitation questions, capability statement requests, or teaming inquiries, reach out directly.