Real Estate
- +0new projects in 2026
- 0hours saved on documents
Measure the impact of AI agent adoption.
FinArch connects agent work, cost, accepted evidence, and model quality checks into a business case your team can review.
Trusted by teams in
Banking & Finance
- +0new assistants
- 0checks without manual review
IT
- 0API integrations
- 0model test cases
Data Centers
- 0monitoring processes
- 0/7ticket control
3D Printing
- +0pilot lines
- 0%faster order preparation
HR
- +0recruiting scenarios
- 0hours saved on routine work
Sales
- +0sales assistants
- 0requests handled faster
Why the platform is useful
Business case without manual spreadsheets
The platform gathers impact, cost, confidence, risks, and the next action for each agent.
Evidence before scale
Value enters the calculation only after review: accept, edit, or reject every claim.
Model quality next to money
Compare models by quality, cost, and latency before changing the setup or expanding the team.
How it works
Three steps to verified impact
FinArch turns agent work into a simple measurement loop: complete the task, calculate value, then let a person verify the result.
- 01Agent completes a task
A real task runs through chat or API Proxy.
- 02The platform records cost and calculates value
FinArch saves model spend and estimates the useful outcome.
- 03The user reviews the result
A person accepts, edits, or rejects the evidence before it counts.
Tune the agent's usefulness
Choose which useful outcome the agent should prove. The platform shows what to inspect, accept, and improve.
Analyze hours and minutes
The platform converts saved minutes into a concrete value estimate and net impact.
Automated report preparation reduced the cycle from two days to one hour.
Evidence preview
12 eventsmanual_review_avoidedSupplier invoice review · 42 min
$38.5082% confidenceaccepted
document_foundContract lookup · 28 min
$25.7076% confidencepending
draft_createdDecision note draft · 18 min
$16.5064% confidenceaccepted
Model quality
Compare quality before scaling
Positive ROI does not prove the model is ready. Compare quality, cost, and latency on this agent's own tasks.
Claude Opus 4.8Anthropic
Quality88%
Latency1.8 s
Cost$3.40
Decisionbest quality for complex tasks
GPT-5.5OpenAI
Quality82%
Latency2.1 s
Cost$2.10
Decisionbalanced analysis and cost
Gemini 3.1 Pro PreviewGoogle
Quality79%
Latency1.5 s
Cost$0.90
Decisionefficient option for simple tasks
Who this solution is for
Finance
See impact, cost, and net result without manual summaries.
Operations
Understand which workflows are ready for a wider pilot.
Product leaders
Compare model quality before changing an agent setup.
Pilot owners
Show what must be fixed before scaling AI work.
Prove AI impact on real work
Bring evidence, cost, and model quality into one business case before expanding the pilot.