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DATA PIPELINES FOR AI

The plumbing nobody demos: document ingestion, retrieval, eval harnesses, and drift monitors.

Engagement

8–12 weeks

Stack

Your choice

Deliverable

Pipelines + evals

The problem

MODELS ARE CHEAP. DATA IS HARD.

Every AI project fails in the same place — not the model, but the retrieval, the grounding, the eval set, the drift detection. The unsexy 90%.

What we build

01
Document ingestion
OCR, layout-aware parsing, table extraction, and PII handling for your specific corpus — PDFs, contracts, filings, scans.
02
Retrieval system
Hybrid search (BM25 + vector + metadata) with re-ranking. Tuned to your recall@k targets, not a vendor demo.
03
Eval harness
A living test suite that runs on every change. Catches regressions before they ship.
04
Drift monitors
Track input distribution, retrieval quality, and output quality over time. Alerts when your world shifts.

By the numbers

8–12

Weeks

Hybrid

Retrieval architecture

∞

Evals run on change

Two-week fixed-fee engagement to map your workflow, quantify the drag, and return a ranked list of automations with expected ROI.