IndyKite.ai is a unified platform that embeds real‑time trust signals into every data access request, enabling fine‑grained, context‑aware authorization for humans, applications, and autonomous AI agents. By evaluating provenance, identity, purpose, and risk scores at the moment of use, it provides continuous auditability, automated compliance reporting, and dynamic policy enforcement across structured and unstructured data stores, allowing enterprises to accelerate AI development while maintaining security and regulatory control.
Funding
$8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
1OFounders
Product
Problem
Enterprises deploying AI face fragmented data silos, static role‑based access controls, and after‑the‑fact governance that hinder rapid innovation while exposing them to compliance and security risks.
Solution
IndyKite provides a unified platform that embeds real‑time trust signals into every data access request, whether made by humans, applications, or autonomous AI agents. By evaluating context, provenance, identity, and purpose at the moment of use, the platform enforces fine‑grained, dynamic policies across structured and unstructured data stores. It delivers continuous decision traceability, automated compliance reporting, and a graph‑based policy engine that adapts as data, risk signals, and relationships evolve. This enables organizations to accelerate AI development, safely share data across teams and partners, and build customer experiences that rely on trusted, contextual information.
Target Audience
Primary customers are large enterprises that run production AI workloads, including data‑intensive teams, AI developers, and B2B partners needing granular, compliant data access.
Features
- Graph‑based knowledge‑base access control (KBAC) that evaluates policies using live context, relationships, and trust scores
- Real‑time, context‑aware enforcement for autonomous AI agents and multi‑agent systems (AgentControl)
- Automated content‑aware tagging and risk classification for unstructured data (e.g., SharePoint) with PII/PHI detection
- Externalized, reusable access policies that unify security across applications, data repositories, and AI pipelines
- Decision audit logs that capture full provenance, policy evaluation, and consent information for compliance (SOC 2, GDPR, HIPAA, ISO 27001)
- APIs and SDKs for seamless integration with existing enterprise stacks and B2B ecosystems
- Scalable cloud-native architecture supporting high‑throughput, low‑latency authorization for large enterprises