The Challenge
With a rapidly growing backlog, the Mid Data Scientist was overwhelmed. The manual nature of the work led to inconsistent outputs and delayed turnaround times, directly impacting the company's ability to scale its Data & Analytics operations effectively.
"A company automated feature engineering, model evaluation reports, and A/B test statistical analysis."
Interactive ROI Model
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Live ModelIncludes salary, benefits, equity, and taxes.
Includes SaaS fees, tokens, and maintenance.
The Solution
The team built a multi-step agentic pipeline using Claude Opus with retrieval-augmented generation (RAG) over their internal knowledge base. The agent ingests context, generates work product, self-evaluates against a rubric, and only surfaces items that need human review.
Productivity Analysis
40hr week, minus PTO, holidays
24/7/365 · No downtime
An AI agent delivers 6,880 additional operational hours per year compared to a human employee — equivalent to hiring 5 additional FTEs.
Key Results
Six months post-deployment, the team hasn't looked back. The agent generates 6,880 additional productive hours annually. The $155k savings funded two new strategic hires in positions that actually require human judgment.
Why This Works
No FICA, FUTA, or state UI taxes.
Eliminate stock grants and vesting liabilities.
No 3-6 month ramp-up period.
Consistent quality with no fatigue.
No health insurance or 401k match.
Scale agents instantly.