Company now supports more connectivity and context types across 10 major categories while continuing to enable BYOC, BYOM, and MCP capabilities
AUSTIN, TX, UNITED STATES, October 29, 2026 /EINPresswire.com/ — Autoptic Inc., an innovator in AI Site Reliability Engineering (AI SRE), today announced an expansion of its ecosystem to 30+ integrations across 10 categories. The update advances Autoptic’s vision of an open, enterprise-capable AI SRE platform that connects operational context, engineering workflows, AI agents, and service systems. Autoptic helps engineering teams understand and manage the latent risks of accelerating software change, preventing complex degradations that too often become incidents.
Autoptic combines cross-provider interoperability with Open Agent Orchestration, Bring Your Own Cloud (BYOC), and Bring Your Own Model (BYOM) deployment approaches. Rather than forcing another toolchain replacement, costly SaaS approach, or centralized telemetry repository, the Autoptic platform is designed to build on existing engineering investments while giving CTOs and their teams greater control over infrastructure, models, and workflows.
Understanding Risk Across System Boundaries
Production risk today rarely demonstrates in a single tool. A deployment recorded in GitHub may coincide with a CloudTrail configuration change, latency detected in Prometheus, growing cloud costs, and an unresolved Jira issue. Each system offers part of the picture; connecting those signals is essential to understanding their operational consequences. The challenge is not simply collecting more data. It is relating change events to system behavior, assessing whether a condition is transient or persistent, and identifying meaningful risks before a customer-facing disruption makes them obvious.
“AI is accelerating software creation and increasing the rate of change across already complex production environments,” said Steve Semelsberger, Co-Founder & CEO of Autoptic. “The next frontier of AI SRE isn’t just resolving incidents faster. It’s understanding how changes interact, recognizing where risk is accumulating, and helping engineering teams act wisely to prevent failures.”
30+ Integrations Across 10 Categories
Autoptic now supports or will soon enable:
+ CI/CD & Repositories: Bitbucket, GitLab, GitHub
+ Collaboration: Slack, Microsoft Teams
+ Coding Tools: Claude, Codex, Windsurf (via MCP Server)
+ Events, Metrics, Logs, Traces: AWS CloudTrail, Amazon CloudWatch, AWS Cost Explorer, Loki, Mimir, Tempo, OpenSearch, Prometheus, VictoriaMetrics
+ Incident Management: Grafana IRM, Incident.io, PagerDuty
+ Issue & Service Management: Jira, ServiceNow
+ LLMs & Inference Providers: OpenAI, Anthropic, Amazon Bedrock, Groq
+ MCP Endpoints: Broad connectivity via agentic workflows.
+ Observability: Datadog, Dynatrace, Grafana, Sentry
+ Single Sign-On (SSO): Google, Microsoft, Okta, Duo
These integrations operate with bidirectional precision. Observability, event, repository, and service management systems contribute evidence about production behavior and change. Collaboration and incident management integrations connect intelligence to established response workflows. Coding, MCP, and model integrations support AI-assisted engineering and inference enablement. SSO integrations enable authentication and access governance.
This breadth empowers Autoptic to correlate context across technical and organizational boundaries, rather than treating incidents, deployments, infrastructure, and operational risks as isolated events.
Open Agents, MCP, and Deterministic Analytics
Autoptic extends beyond its named integrations through the Autoptic MCP Server, enabling interoperability with additional Model Context Protocol-compatible AI clients and engineering environments. Supported Autoptic capabilities can be surfaced in workflows using tools such as Claude, Codex, and Windsurf, giving teams flexibility to work with AI SRE from familiar development environments.
Within the Autoptic platform, Open Agent Orchestration combines AI Agents, reusable Skills, and deterministic Tools. Autoptic’s Performance Query Language (PQL) supports repeatable anomaly analysis across federated operational sources, while AI agents coordinate forensics and interpret results. This approach balances the adaptability of language models with the computational precision required for complex production telemetry. Federated access also helps avoid unnecessary duplication of high-volume observability data, allowing organizations to preserve established systems of record while drawing on them for richer analysis.
“Connecting to enterprise data is only the first step,” said Peco Karayanev, Co-Founder and CTO of Autoptic. “The difficult work is scoping and aligning signals from systems with different data models, access patterns, authentication, time horizons, and semantics, all at scale. Autoptic combines federated access, deterministic computations, and agent orchestration so engineers can reason across boundaries without surrendering control of their existing architecture.”
Moving From Incident Response to Preventative Risk Management
The integration expansion reinforces Autoptic’s recently introduced Risks module, designed to help engineering teams explicitly identify, assess, and manage latent production risk over time. Autoptic’s three core experiences work together: Briefs proactively detect anomalies and emerging degradations; Investigations help engineers examine complex behavior using connected evidence and AI-assisted reasoning; and Risks provides a structured view of persistent trends and changing operational exposure.
For example, a gradual performance decline may reflect an interaction among an infrastructure change, shifting workload, unresolved engineering debt, and a third-party dependency. Bringing these signals together can help teams prioritize preventative action instead of waiting for the next incident. This shifts the operational conversation from asking only what broke and how quickly to restore it, toward asking what is becoming fragile, why, and where engineering effort can reduce future exposure.
Enterprise Choice Through BYOC and BYOM
Autoptic is primarily deployed through a BYOC model, allowing deployment within customers’ own cloud environments. It also leverages a BYOM approach, enabling choice among supported commercial and open-source language models and inference providers. Together with federated data access, enterprise SSO, and MCP interoperability, these options help organizations align AI SRE with security, governance, cost, and deployment requirements. For CTOs, the combination offers an alternative to rigid AI SRE architectures that dictate where sensitive operational information must reside or which model provider must be used.
About Autoptic
Autoptic is collaboratively designing and building the practice of Systems Change Resilience, helping CTOs and software engineering organizations move faster, absorb more change, calibrate risk, and build stronger software systems in an increasingly complex, AI-fueled world. Autoptic integrates with 10 categories of AI, infrastructure, DevOps, ITSM, and other systems to help engineering teams detect production anomalies earlier, investigate complex environments faster, reduce incident risk, and better manage operational costs. The company was co-founded by software industry veterans and is backed by 35 professional investors, including 9 CTOs. Launched in 2026, Autoptic has already been named one of five “Cool Vendors” by Gartner in AI for IT Operations and one of 12 “Austin Startups to Watch” by the Business Journal. For more information, please visit www.autoptic.ai
Steve Semelsberger
Autoptic Inc.
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