Agents and workflows
Claims automation, citizen services and operational agents completing real work.
Case Studies
Case Studies by Solution
Find proof points for the capability you want to ship next.
- 6solution families with proof
- 16detailed case studies
- 100%in production, not pilots
Browse
Case studies by solution type
Browse success stories by solution type — agents, RAG, copilots and more.
Enterprise RAG
Knowledge assistants and research platforms grounded in enterprise truth.
Copilots and CX
Employee and customer-facing systems with measured adoption.
Platforms and ops
The infrastructure builds that made everything else faster.
Patterns that repeat
What the successful deployments share
Read across the case studies and the same success factors recur — regardless of industry or solution type.
Pattern one
Evals before ambition
Every successful system had its golden set and quality gates before scale-up. The claims platform, the knowledge assistant, the research tools — all expanded only as measured quality held.
- Golden sets built from real cases first
- Expansion gated on scores, not enthusiasm
- Drift caught by monitoring, not complaints
Groundedness
96%
Safety
100%
Task success
93%
Tone & format
91%
CI gate passedrelease promoted to production
Pattern two
Integration depth beats model choice
The differentiator was never which model — it was wiring into Guidewire, Epic, CMMS and order systems so AI could act. Systems that only answered plateaued; systems that acted transformed metrics.
- Actions in systems of record, with guardrails
- Idempotent, validated writes throughout
- Escalations carrying full context to humans
SalesforceSlackSAP
JiraSSnowflake
ServiceNowTeamsDrive
OAuthSSOPermissions-awareReal-time sync
Pattern three
Trust is a feature you build
Citations, visible confidence, human gates and honest 'I don't know's drove adoption everywhere — the technical accuracy mattered less than users' ability to verify it.
- Citations on every consequential answer
- Human sign-off where stakes demand it
- Transparency that turned skeptics into users
✓PII detected & redactedenforced
✓Answer grounded in sourcespassed
✓Role-based data accessenforced
✕Out-of-scope tool callblocked
SOC 2GDPRAudit logHITL
Jump in
Start with your solution need
Workflow automation
Claims Automation — multi-agent processing at scale.
Knowledge systems
Knowledge Assistant — ACL-aware RAG for 20K users.
Customer support
Support Agent — 70% resolution, CSAT up.
Employee experience
Support Copilot — queues halved, 85% adoption.
Decision support
Demand Intelligence — forecasts planners trust.
Industrial AI
Operations Copilot — downtime down 37%.
Delivery
From challenge to outcome
We publish the architecture decisions, delivery approach and measurable results — so you can see how similar outcomes could apply to your enterprise.
- Measurable KPIs
- Architecture transparency
- Cross-industry patterns
- Repeatable playbooks
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1
Challenge
Business pressure, legacy process and constraints.
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2
Solution
Architecture, agents and integration design.
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3
Delivery
Build, evaluate, secure and launch.
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4
Impact
Efficiency, cost, quality or revenue outcomes.
FAQ
Common questions
Which solution type delivers fastest?
Support automation and knowledge assistants typically show measurable results in one quarter; workflow automation follows close behind. Platform investments pay back through every subsequent build.
Do these use the same underlying architecture?
They share foundations — retrieval, evals, guardrails, observability — with solution-specific layers on top. That reuse is why later engagements move faster.
How current are these case studies?
All are from recent production deployments and updated as programs expand. Ask us about the current state of any of them.
Next step
Match a pattern to your problem
Describe the workflow — we'll point you to the closest proven build and its numbers.