Autonomous Agents That Surface What Matters
Deploy custom agents tailored to your business goals. Audit SOPs for drift. Understand why SLAs are failing. Measure AI adoption. Surface automation opportunities. Every finding is evidence-backed and dollar-quantified.
Out of the Box Autonomous Agents
Pyze agents are configured to your specific objectives. Tell us what you need to understand, and an agent will continuously analyze execution data to surface answers.
Audit SOPs for Drift
Continuously compare actual execution patterns against documented procedures. Surface when teams deviate from SOPs — and quantify the impact on quality and efficiency.
Understand Why SLAs Are Failing
Decompose SLA breaches into root causes — handoff latency, rework loops, system bottlenecks, or staffing gaps — with evidence from actual execution data.
Discover AI Opportunities
Mine execution patterns to identify where AI agents can augment or automate work. Score each opportunity for readiness and projected impact. Learn more →
Measure AI Adoption & ROI
Track whether AI tools are actually being used, and whether adopters outperform non-adopters. Prove ROI with execution data, not surveys. Learn more →
Benchmark Workforce Productivity
Identify how top performers differ from average — by handling time, context switches, tool usage, and process adherence. Scale best practices across teams and geographies.
De-Risk Legacy Modernization
Capture undocumented business rules from how staff actually use legacy systems. Discover what to migrate before you touch the code.
From Finding to Fix
Every finding is an evidence-backed business case with dollar quantification and a four-stage governance lifecycle.
Surfaced
Agent identifies an opportunity with evidence and savings estimate
Accepted
Operations team reviews the evidence and commits to action
Remediating
Fix is in progress — tracked across teams and geographies
Remediated
Impact measured against baseline — savings validated
Evidence-Based, Risk-Adjusted
Every savings estimate is risk-adjusted across four dimensions: detection confidence, implementation feasibility, adoption readiness, and compliance path. What you see in the dashboard is what you can defend to leadership.
30%
Pattern Frequency
30%
Decision Complexity
20%
Data Structure
20%
Cross-App Scope
Open by design
Plug into your agent stack
Pyze agents don't just observe — they connect. A Model Context Protocol (MCP) server exposes the live execution model, the network baselines, and the machine-checkable SOPs to your own agent frameworks, so the AI you deploy can ground its decisions in how the work is actually done and write outcomes back for continuous measurement.
- ✓ Standardized MCP endpoint — governed, real-time access for agents
- ✓ Tools for metrics, conformance, opportunities, and SOP retrieval
- ✓ Closes the loop with AI Effectiveness — every agent action is measured against the baseline
See What Your Agents Would Find
Deploy Pyze's autonomous agents on your workflows and see quantified opportunities within weeks.