Planto provides an operating system for enterprise AI agents, offering a governed runtime with persistent memory, policy enforcement, and full decision lineage. The platform enables organizations to deploy, manage, and audit autonomous agents across their operations with enterprise-grade security and compliance controls. Planto's Medhara core delivers structured memory with provenance, capability-based access control, and deterministic traceability for every agent action.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises deploying AI agents face immediate governance and compliance risks, as there is no standard runtime that enforces boundaries around agent behavior. Agent systems lack auditability—when something goes wrong, reconstructing the decision chain requires manual log correlation across fragmented tools. Additionally, operational control is fragmented, with each team building their own guardrails, leading to inconsistent policy enforcement and undefined security boundaries where agents operate with ambient authority.
Solution
Planto provides PlantoOS, a unified compute layer and operating system purpose-built for the agentic era, offering the runtime, memory, and access controls required for enterprise-grade agent systems. The platform delivers a governed runtime with persistent memory across sessions, capability-based governance through deny-by-default policies, and full decision lineage that links every action to its trigger, data sources, and outcomes. Planto's Medhara core transforms raw observations into structured facts and distilled intuitions through a crystallization pipeline, while the Enterprise OS product provides a unified control plane for managing agent execution across tools and systems. The platform includes industry-specific solutions for BFSI, healthcare, financial services, customer support, and manufacturing, with applications ranging from coding assistants to compliance and decision intelligence tools.
Target Audience
Primary customers are enterprise organizations in BFSI, healthcare, financial services, manufacturing, and customer support that need governed, auditable AI agent deployments with persistent memory and compliance controls.
Features
- Unified control plane for orchestrating agent execution across tools, systems, and policies with real-time monitoring of latency, token usage, and cost per run
- Medhara memory core with typed memory objects featuring versioning, TTL, scope, and provenance chains, plus a crystallization pipeline that transforms raw observations into structured facts
- Capability-based governance with deny-by-default policies across six hierarchical layers (Org, Team, Project, Agent, Tool, Action) with override capabilities
- Full decision lineage with deterministic traceability linking every agent action to its trigger, data sources, policies, and outcomes via trace IDs and span IDs
- Policy stack with 34+ active rules supporting token limits, audit trail requirements, data masking, query limits, and action gating with version control
- Memory explorer with 1,247+ searchable objects including facts, observations, decisions, and intuitions with confidence scores and retention policies
- Enterprise-grade security with AES-256-GCM encryption, auto-archiving after 90 days of inactivity, and PCI compliance support for sensitive data handling
- Industry-specific agent applications including fraud detection, loan decision assistance, clinical documentation, manufacturing incident intelligence, and sales intelligence