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Case studies

Anonymized engagements, real numbers. Each one is production software the client’s team has owned for at least six months.

B2B SaaS · Late-stage workflow-automation SaaS

Multi-tenant inference platform: 71% cost reduction at 4× the traffic

An internal inference platform for a SaaS company. Continuous batching, semantic caching, KV-cache reuse, model routing, per-tenant cost attribution. Built so the CFO can read the dashboard.

Sep 15, 2025 · 9.4M requests/day · 38 customer tenants · p99 < 2.1s · 99.97% uptime

SaaS · B2B SaaS, ~50k seats

Customer-facing support copilot, deflecting 38% of L1 tickets

A grounded copilot embedded in a SaaS product's help center — answers from real docs, escalates honestly when it doesn't know, and stays on-brand.

Jul 15, 2025 · 1.2M monthly conversations · p95 < 1.5s · 99.95% uptime

HR technology · Series-C HR-tech platform

Recruiting pipeline: 6× recruiter throughput, without the spam

Inbound resume parsing, structured screening, and outreach drafting. With hard guardrails against the auto-spam failure mode that has tarred the category.

Jul 9, 2025 · 180k resumes/month · 4,200 active reqs · p95 screen-to-draft < 8s

Finance & operations · Mid-market manufacturing group, 9 operating units

AP invoice intake: 92% touchless processing across 14 ERP destinations

We replaced a 22-person offshore keying team with a deterministic, eval-gated pipeline. OCR plus structured extraction, vendor-policy routing, human review on the rows that need it, idempotent ERP writes.

Feb 12, 2025 · 210k invoices/month · 14 ERP destinations · p95 turnaround < 90s

Financial services · Mid-market financial research firm

Sub-second semantic search across 12M financial filings

RAG over a decade of regulatory disclosures, serving an internal research team. Cut analyst time-to-answer from minutes to seconds with measurable retrieval quality.

Dec 15, 2024 · 12M documents · 280k queries/month · p95 < 800ms

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The case studies above are the ones we have permission to publish. We’ve done others. Send us a description; we’ll tell you whether we’ve done something similar and what we learned.