The Trust & Governance Layer for Autonomous AI Systems
As AI agents transition from supervised assistants to autonomous decision-makers, enterprises require uncompromising runtime observability, policy enforcement, and auditability.
The Shift to Autonomous AI
Why traditional LLM monitoring is insufficient for modern multi-agent systems
Supervised LLM Chains
- ✕Point-in-time token counts without agent identity mapping
- ✕Post-hoc alert delivery after unsafe execution runs
- ✕Siloed observability tied to single SDK frameworks
The Agentis Control Plane
- Real-time runtime interception & hard blocks in 0ms
- Unified OpenTelemetry agent inventory across all frameworks
- Immutable, audit-ready compliance evidence bundles
The Four Pillars of Agentis
A complete, layered architectural model for autonomous enterprise AI
Visibility & Compliance Graphs
Complete mapping of every agent node, tool call, memory retrieval, and external API egress. Agentis generates live directed acyclic graphs (DAGs) illustrating exactly how autonomous decisions propagate across your infrastructure.
Intelligence & Economic Observability
Granular, span-end cost calculation across 2,500+ foundation models. Attribute AI spend directly to specific business workflows, customer accounts, and agent versions without sampling errors.
Control & Governance-as-Code
Deterministic guardrails defined as declarative policies. Stop unauthorized model usage, recursive execution loops, and data exfiltration before irreversible database changes or financial actions execute.
Certification & Trust
Automated generation of compliance documentation mapped to the EU AI Act (Articles 12, 14, and 50) and HIPAA 45 CFR regulations with cryptographic integrity verification.
Built on Enterprise Cloud Infrastructure
Engineered for sub-millisecond telemetry ingestion, petabyte-scale time-series graphs, and seamless AWS Activate and enterprise cloud deployment.
AWS Bedrock & SageMaker
Direct native auto-instrumentation for Amazon Bedrock models (Titan, Claude, Llama 3) and Amazon SageMaker endpoints with zero proxy overhead.
Amazon EKS & Serverless
Distributed trace collectors running across Amazon Elastic Kubernetes Service (EKS) and AWS Lambda event streams processing billions of events monthly.
OpenSearch & Vector DBs
High-dimensional embedding trace analysis utilizing Amazon OpenSearch Vector Search and distributed ClickHouse clusters for real-time span queries.
AWS KMS & S3 Vault
Hardware-backed cryptographic security using AWS Key Management Service (KMS) and write-once-read-many (WORM) S3 Object Lock compliance trails.
Agentis is built for venture-backed teams and accepts credits from AWS Activate, Google for Startups, and Stripe billing integrations.
Founding & Executive Team
Veteran distributed systems engineers, cloud architects, and AI researchers dedicated to enterprise agent reliability
Khushal Thakkar
Directs product strategy and enterprise architecture. Specializes in autonomous multi-agent topologies, OpenTelemetry standards, and cloud-scale infrastructure.
Ananya Rao
Leads declarative runtime policy research, EU AI Act compliance mapping, and evaluation harness designs across foundation model benchmarks.
Marcus Sterling
Oversees multi-region Kubernetes deployments, AWS PrivateLink routing, SOC-2 compliance operations, and zero-trust telemetry ingestion pipelines.
Ready to govern your AI agents?
Start with our open-source OpenTelemetry SDK or deploy the complete enterprise control plane.