Proof

One big number. And how we measured it.

Every case study here reports its golden-set size, its inter-annotator agreement, and both the benchmark number and the unseen-data number — because the gap between those two matters more than either alone. Where an NDA blocks the client's name, we describe them specifically; we never invent one.

Showing 7 results for All.

Logistics warehouse illustrating freight invoice operations
Client Case StudyLogisticsAI Assurance
83%recall at 96% precision

Freight invoice discrepancy detection for a European 3PL

A document-intelligence agent reconciles freight invoices against TMS data and carrier records, moving the operation from manual sampling to full-volume coverage.

  • 340-case golden set
  • 100% invoice coverage
View Case Study
Enterprise knowledge assistant for internal policy and SOP automation
Client Case StudyAI Assurance
~500daily questions deflected

Enterprise knowledge assistant for internal policy and SOP access

An internal assistant answers recurring HR and administration questions from approved policies across a multi-company group.

  • 5,000+ employees
  • 15+ subsidiaries
View Case Study
Inventory-aware B2B ordering and product recommendation chatbot
Client Case StudyHealthcare
3,000B2B customers served

Inventory-aware B2B ordering and product recommendation agent

A conversational agent handles order intake and inventory questions, validating live stock before committing an order.

  • Live inventory validation
  • Conversational order intake
View Case Study
Practice BriefFinancial ServicesAI Assurance
Audit-readydelivery artifacts and controls

Governed AI delivery for financial-services workflows

A delivery pattern for document intelligence, fraud and AML workflows, and internal copilots that need traceability from model output to second-line review.

  • Client-tenancy deployment
  • Evaluation and governance evidence
Explore Financial Services
Instruction-based image editing and refinement dataset
Delivery BriefAI Data

Instruction-based image editing and refinement dataset

Structured examples pair source images, edit instructions, and reviewed outputs for training and evaluating instruction-following image systems.

  • Instruction-following coverage
  • Review-ready examples
Explore AI Data
Agent online correction and reasoning alignment dataset
Delivery BriefAI DataAI Assurance

Agent online correction and reasoning alignment dataset

Human-reviewed correction traces capture where an agent deviates, how it is repaired, and which reasoning pattern should be reinforced.

  • Failure-mode taxonomy
  • Correction and preference signals
Explore AI Data
Computer-use agent trajectory dataset
Delivery BriefAI Data

Computer-use agent trajectory dataset

Action trajectories connect interface state, agent decisions, outcomes, and recoverable failure points for computer-use training and evaluation.

  • Action and state sequences
  • Outcome and recovery labels
Explore AI Data

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Your workflow could be the next one here.

Six weeks, fixed timebox, thresholds agreed in week one — and if the system doesn't clear them, the final 30% isn't due.