Empirik.ai provides an AI agent that captures engineer intent at the source of infrastructure changes—such as pull requests, tickets, or pipelines—and maps it against a continuously updated graph of the live environment to compute blast radius before changes land. The platform helps teams prevent incidents, resolve failures faster, and maintain production assurance across cloud, on-prem, and SaaS systems.
Funding
$21M 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.
Founders
Product
Problem
Engineering teams struggle to predict the impact of infrastructure changes before they are deployed, often discovering failures only after they reach production. The complexity of modern, distributed environments makes it difficult to trace dependencies across cloud, on-prem, and SaaS systems, leading to costly incidents, prolonged downtime, and wasted resources on orphaned infrastructure.
Solution
Empirik.ai provides an AI agent that captures engineer intent directly where a change originates—such as a pull request, change ticket, or pipeline—and maps it against a continuously updated, compiled graph of the live application environment. The agent computes the blast radius of a proposed change, showing affected services, owners, and evidence before approval. It also supports post-change analysis by replaying changes to identify root causes of incidents, and continuously reconciles intended, deployed, and runtime state to flag unauthorized changes and operational drift. The platform is provider-agnostic, integrating across cloud, on-prem, and SaaS systems, and can be deployed as a SaaS offering or inside a customer's VPC.
Target Audience
Primary customers are enterprise platform and infrastructure engineering teams who need to manage complex, dynamic cloud and application environments with high reliability and compliance requirements.
Features
- Blast radius analysis that projects pull requests and change requests onto the actual environment, ranking affected services and providing rollback context
- Continuous production assurance that reconciles intended, deployed, and runtime state, tracing divergences to their source and operational impact
- Unauthorized change detection that identifies changes landing outside approved paths, along with the actor, time, and approval gap
- Waste reduction capabilities that find orphaned and idle infrastructure, identify owners, and generate safe removal plans
- VM dependency mapping that visualizes processes, services, listeners, and network paths behind every VM before migrations or changes
- AI-powered intent parsing using locally deployed Llama3 for graph crawling and Cypher query generation, ensuring no data leaves the customer-controlled environment