AI-powered enterprise intake and process orchestration platform
High-assurance infrastructure for AI agents
Stage
Not given
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Founded
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Based in
US
US
Pricing model
Contact for pricing
Open source
Pricing
Custom pricing based on Monthly Tracked Users (MTUs) and deployment options. The platform includes unlimited workflows, connectors, data, and automation. Optional single-tenant dedicated, customer cloud-hosted, and customer-hosted on-prem hosting available for Enterprise customers at additional cost
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Key features
Agentic Orchestration Engine with agent autonomy, deterministic process logic, and context graph
Unified Control Plane to manage all processes across departments, people, AI, and systems
Enterprise-Grade Runtime for mission-critical processes with governance and compliance
No-Code Process Builder with drag-and-drop workflow tools
Data Source Integrations connecting 250+ applications
Enterprise Agents for specialized tasks like procurement, legal, and invoicing
Real-time dashboards and operational visibility
Collaborative Intake for tailored request handling
Contracts Hub for AI-native contract orchestration
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
Most comprehensive agentic orchestration platform purpose-built for enterprise AI adoption at scale
Enables non-technical process owners to deploy and refine AI agents without IT involvement
Integrates with 250+ enterprise applications without requiring replacement of existing systems
Proven track record with enterprises achieving 2.2X adoption increase and 50% cycle time reduction
Ensures enterprise governance, compliance, and audit controls for mission-critical processes
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
Tonkean
Perseus Computing