The Enterprise Agent Build & Runtime for the work your business runs on
High-assurance infrastructure for AI agents
Stage
Not given
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Founded
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Based in
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US
Pricing model
Freemium
Open source
Pricing
Free plan with 50 workflow executions per month and visual editor. Enterprise plan with custom pricing includes governance, dedicated VPC, and comprehensive support.
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Key features
Visual editor and AI copilot
No-code visual editor, exportable to Python
Code-first API built for total control
Real-time tracing of every LLM call, tool call, and memory read
RBAC and audit with immutable audit trails and Enterprise IAM
Human-in-the-loop approval gates and intervention during execution
Runtime hooks inject PII redaction and policy checks
Automated and human-guided training for continuous improvement
Multi-LLM testing for model swapping at runtime
GitHub integration
Harpe: chooses what an AI agent reads under a token budget with consistent results
Kibisis: keeps agent memory on your hardware with AES-256-GCM encryption
Argus: append-only record that detects edits with cryptographic verification
No network code by default for local and disconnected use
MIT License with published code, benchmarks and raw results
What makes it different
Agentic use case generator powered by billions of agent runs
Intelligently guided by 700k agent workflow patterns
Control Plane sits in execution path ensuring every agent interaction is observable, compliant, and reversible
Every production run turns into training data to sharpen accuracy and save money
Measured empirical validation across 6,111 questions outperforming full-context models
Zero plaintext on disk with encrypted vaults matching plaintext accuracy
78.3% fewer tokens sent to the model with a 1,200-token budget per turn
Preserves conversational chronology and relational qualifiers under token budgets
Perseus Computing