Akhara
Akhara provides a runtime verification layer for AI agents in regulated enterprises, checking each proposed action against encoded policies, enterprise records, and expert judgment before execution. The platform returns confidence-scored verdicts in milliseconds, allowing, warning, blocking, or escalating actions to prevent policy violations before they reach production. Its proving ground environment replays real-world workflows to generate release evidence and quality scores for agent trajectories.
- Regulatory & Compliance Technology
- Artificial Intelligence
- AI Agents
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Non-deterministic AI agents are increasingly assigned deterministic, high-stakes work in regulated enterprises, yet their behavior drifts in ways that are difficult to detect or reproduce. Existing observability tools only catch violations after the fact, when the agent has already acted, leaving organizations unable to trust or govern autonomous systems in compliance-critical domains.
Solution
Akhara operates as a verification layer that runs inside the runtime, checking each proposed agent action before it executes. The platform encodes statutes, regulations, and internal policies into machine-checkable constraints, grounds verification in enterprise knowledge bases and systems of record, and elicits ground truth from credentialed experts whose judgment was never written down. Every step is evaluated in milliseconds against these sources, returning a verdict with a confidence score that allows, warns, blocks, or escalates the action. This real-time checking makes agent drift reproducible and verifiable, enabling regulated enterprises to grant agents autonomy with governance.
Target Audience
Primary customers are regulated enterprises across sectors such as healthcare, finance, and legal that deploy AI agents for high-stakes work and require verifiable compliance with laws, policies, and institutional knowledge.
Features
- Runtime-embedded verification that checks each proposed action against regulation, enterprise records, and expert judgment before execution
- Ground truth engine that combines encoded laws and policies, embedded knowledge bases and systems of record, and elicited expert judgment into one auditable source of truth
- Domain-specific reinforcement learning environments that replay real-world, high-stakes workflows for continuous drift testing
- Expert network that sources, verifies, and manages hundreds of licensed domain experts (clinicians, scientists, operators) within days
- Verdict system returning confidence scores with allow, warn, block, and escalate actions in milliseconds
- After-the-fact log reconstruction replaced with proactive, real-time intervention that blocks policy violations before they reach production
- Visual test authoring for non-engineers, enabling teams to create and manage verification scenarios without coding
- Execution trace replay showing conversation, tool calls, and resulting state for each evaluated trajectory