Production AI Agent Results and ROI
What are AI agent ROI metrics?
AI agent ROI is measured by cycle time, throughput, accuracy, rework rate, exception rate, compliance coverage, token efficiency, and cost per completed workflow. In production deployments MightyBot delivers 70%+ less processing time and 80% fewer manual interactions, 99%+ accuracy and 10x throughput per loan administrator in the flagship lending deployment, and 95% less time on task in the Built Technologies draw agent deployment.
Production Metrics
What AI agent ROI metrics measure
| Metric | What it measures | How it is computed |
|---|---|---|
| Cycle time | Elapsed time per completed workflow | Timestamped start to finish |
| Throughput | Completed workflows per person per period | Count over interval |
| Accuracy | Agreement with verified ground truth | Sampled double-review |
| Rework rate | Share of outputs requiring correction | Corrections over completions |
| Exception rate | Share routed to humans | Exceptions over total |
| Compliance coverage | Share of decisions with complete audit trails | Traced over total |
| Token efficiency | Model spend per completed workflow | Tokens over completions |
| Cost per completed workflow | All-in cost over completions | All-in cost over completions |
Customer Proof
Real clients. Real results.
Built Technologies is the leading construction finance technology platform. Many financial institutions. $100B+ in construction lending activity.
- 95% less time on task in the Built draw agent deployment
- Draws to borrowers up to 60% faster
- 10x throughput per loan administrator
- Risk issues confirmed by human reviewers
- Seamless integration with no re-architecture
"MightyBot's platform seamlessly integrated into our tech stack without any re-architecture... reducing time on task by nearly 95% and reducing manual steps by 60%."
Thomas Schlegel, VP of Engineering at Built
- Automated extraction across hundreds of statement formats
- Dramatic reduction in time from receipt to proposal
- Higher accuracy on fee breakdowns and savings calculations
Every system becomes an input and an output.
ROI Framework
Calculate your Return
Current cost per transaction
Hours x fully loaded hourly cost + error remediation + LLM token costs.
MightyBot-assisted cost
Apply the 70%+ processing-time reduction and 80% fewer manual interactions measured in MightyBot production deployments.
Annual savings
(Current - Assisted) x annual volume.
Model cost
Compiled plans avoid repeated prompt loops. The July 2026 agent evaluation cost study measures cost per decision cycle for each architecture.
For most regulated workflows, time savings alone justify the investment. Calculate your TCO.
Methodology
How we measure.
Last updated: October 4, 2026
Accuracy
Every extraction and policy evaluation is compared against validated ground truth. 99%+ accuracy in the flagship production lending deployment, which spans 200+ financial institutions and $100B+ in lending activity.
Speed
Processing time from initiation to completion: 70%+ less processing time in MightyBot production deployments, and 95% less time on task in the Built Technologies draw agent deployment. Time on task measures active human work.
Token Efficiency
The July 2026 agent evaluation cost study measures tokens and cost per decision cycle for single-pass, agentic and voting architectures.
Risk Detection
Issues flagged by MightyBot are confirmed by human reviewers. Report only risks verified in subsequent review.
Related pages
Put the metrics in context
Compare the platform, use cases, and economics behind production AI agent results.
This is the new standard for regulated automation. We set it.
FAQ
Frequently Asked Questions
What accuracy do AI agents achieve in production?
Accuracy depends on the workflow and its verified ground truth. MightyBot reports 99%+ accuracy in its flagship production lending deployment. Across production deployments it reports 70%+ less processing time and 80% fewer manual interactions; the Built Technologies draw agent deployment reports 95% less time on task.
How does MightyBot achieve higher accuracy than manual review?
It evaluates every data point against every applicable policy on every transaction. No fatigue. No triage shortcuts. Manual reviewers are effective, but under time pressure they are inherently incomplete.
What are AI agent ROI metrics?
AI agent ROI metrics include cycle time, throughput, accuracy, rework rate, exception rate, compliance coverage, token efficiency, and cost per completed workflow. Model your own workload with the AI agent ROI calculator at /tools/ai-agent-roi-calculator/.
How quickly do results appear?
Speed and throughput improvements show up when transitioning from Audit to Assist, typically within 30 days. The metrics on this page reflect steady-state production performance.
Do results scale with volume?
Yes. Per-transaction metrics remain consistent as volume increases. Volume scales with compute, not headcount.
Can I verify these metrics independently?
Yes. MightyBot's audit infrastructure provides complete traceability, and reference calls with Built Technologies and RocketFee are available on request.