Ship agents into systems you can't afford to break
High-assurance infrastructure for AI agents
Stage
Not given
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Founded
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Based in
IL
US
Pricing model
Freemium
Open source
Pricing
Free plan includes 125,000 tasks and 75,000 triggers monthly with 5 seats and 1 on-prem agent. Starter: $29/month or $24/month billed annually. Business: $289/month or $240/month billed annually. Enterprise: custom pricing.
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Key features
MCP server for AI agents and assistants
Python and TypeScript SDKs
REST API and CLI for scripts and coding agents
No-code workflow canvas
Managed authentication to connected systems
Audit trail of agent actions
Tool permissions scoped per agent
On-premises agent for systems behind firewall
Native integrations with Zendesk, Intercom, Freshdesk, ServiceNow, SAP, NetSuite, Salesforce
Root cause analysis and backend execution of fixes
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
Secure enterprise-grade controls including granular tool permissions, audit trails, and versioning without sacrificing automation speed
Autonomous AI agents that execute fixes end-to-end rather than just deflecting to chatbots or escalations
Multiple interface options including MCP, SDKs, API, CLI, and no-code canvas for different developer and non-developer needs
On-premises deployment capability for regulated or sensitive systems behind firewalls
Seamless integration with entire enterprise tech stack including ERP, CRM, helpdesk, and observability platforms
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
Engini
Perseus Computing