Thira
Thira provides a continuous-learning agentic AI platform that autonomously executes enterprise IT workflows across identity, HR, and service desk systems. Its agents build a living context graph of roles and entitlements, resolve tickets end-to-end, and operate under AI-native governance with audit trails and earned autonomy. The platform reports defensible ROI metrics like hours saved and cost per ticket, reconciled against execution records.
- AI Agents
- Enterprise Software
- Artificial Intelligence
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Enterprise back-office operations rely on repetitive manual workflows across disconnected systems, leading to inefficiencies, errors, and high operating costs. Existing automation tools lack the intelligence to adapt, govern themselves, and operate securely across complex enterprise environments.
Solution
Thira builds secure, self-governing agentic AI that runs enterprise back-office systems autonomously. Its self-learning agents improve over time by analyzing outcomes and adjusting their behavior. Thira learns how an enterprise actually runs by connecting to identity providers, HR systems, service desk tools, knowledge bases, and documents, then builds a living context graph that models roles, entitlements, and workflows. Agents execute end to end within systems of record, diagnose root causes, verify fixes, and hand off to humans only when policies require approval. The platform embeds AI-native governance into every action, ensuring policy enforcement, approval workflows, and audit trails are maintained automatically. Thira reports defensible ROI metrics, including hours saved and cost per ticket, reconciled against a complete execution audit trail.
Target Audience
Thira targets enterprise CIOs and IT operations leaders with complex back-office workflows spanning identity, HR, and service desk systems. The initial focus is on enterprise IT processes and the office of the CIO.
Features
- Self-learning agents that continuously improve performance based on operational outcomes and feedback loops
- AI-native governance layer that embeds policy enforcement, approval workflows, and audit trails into each agent action
- Enterprise context graph that maps roles, entitlements, and process dependencies across systems
- Direct execution inside systems of record including Okta, Entra ID, Workday, Freshservice, and ServiceNow
- Earned autonomy model where agents expand their scope only after building a track record and receiving team sign-off
- Simulation mode that runs workflows end to end without writing to production systems
- Preemptive remediation that monitors applications and access continuously to resolve issues before users notice