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Anyshift

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AI SRE agent that investigates production incidents by tracing changes across a versioned infrastructure graph to find root cause.

Anyshift is an AI platform for cloud infrastructure reliability built around a digital twin, a versioned resource graph of your entire stack, that its agent Annie uses as a source of truth for root cause analysis, proactive risk detection and infrastructure knowledge. When an incident fires, Annie traverses the graph across code deploys, infrastructure changes and monitoring signals to isolate the failure point and answer questions like what changed, with sources, in seconds.

Its Incident Prevention product, a Terraform Superplan, integrates into pull requests to preview the impact zone, dependencies and risk of IaC changes before deployment, preventing outages from things like accidental resource deletion. Anyshift integrates with cloud providers, Git repositories and Terraform state and is led by founder and CEO Roxane Fischer.

Vendor details

Canonical URL

https://anyshift.io

Category

SRE / DevOps agent

Company status

independent

Use cases & customers

Primary use cases

infrastructure root cause analysisincident preventionTerraform change impact analysisproactive risk detection

Target customers

SRE teamsplatform engineering teamsDevOps teams

Deployment options

SaaS (connects to your cloud and Git)

Integrations

Cloud providers, Git repositories and Terraform state files unified into a resource graph.

Sources & related URLs

Agentic Index coverage score

8.5 / 14 capabilities · 61%

Integrations & Tool Calling Full

Integrates with cloud providers, Git repositories and Terraform state files into a unified data model, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Workflow Orchestration Full

Its agent Annie traverses a versioned resource graph across code deploys, infrastructure changes and monitoring signals to run investigations, including parallel investigations in Slack, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Knowledge Grounding & RAG Full

Uses a digital twin, a versioned resource graph of the entire stack, as a source of truth to deliver senior-SRE-level root-cause insight with sources, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Human Oversight & Guardrails Full

Positions AI as leverage on human expertise rather than a replacement, delivering RCA with sources and PR impact reviews for engineers to decide on, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Security, Identity & Governance Partial

Reads infrastructure state and flags risks such as security-patch bypasses, though specific security certifications are not documented, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Observability & Auditability Partial

Gives visibility and auditable RCA with sources through a versioned resource graph, layered over your existing monitoring signals rather than its own telemetry, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Memory & State Persistence Partial

Maintains a versioned resource graph capturing historical infrastructure state, though not a learning memory of past incidents, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Deployment & Data Residency Partial

SaaS integrating with your cloud accounts and Git repositories; self-host or residency options are not documented, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Prebuilt Agents, Templates & Packs Partial

Ships packaged products like Incident Prevention and a pull-request bot rather than a broad prebuilt agent library, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Triggers & Channel Coverage Full

Fires on incidents to isolate the failure point, runs automatically on pull requests to analyze IaC changes, and proactively scans for risks like missing monitors, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Model Flexibility & Routing Unable to verify

No customer facing model choice or routing documented, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

APIs, SDKs & MCP Extensibility Partial

Integrates via pull requests and Terraform state with a queryable resource graph, though a public API, SDK or MCP surface is not detailed, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Testing, Debugging & Optimization Partial

Previews change impact, blast radius and risk before deployment, a pre-deployment validation loop rather than an agent evaluation harness, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

Browser & Computer Use Unable to verify

Operates through Slack, pull requests and a queryable graph rather than browser or computer interface control, Anyshift site 2026-07-22

Sourceanyshift.ioread 2026-07-22

The Agentic Index coverage score grades every vendor Full, Partial or Unable to verify against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded

Pricing

Contact sales (early stage)

Trial available

What is public

No public pricing; early-stage IaC reliability startup, demo-based onboarding.

Variable cost rationale

No public pricing; early-stage and sales quoted.

Sales call required

Mixed (some tiers require a call)

Free / trial

Demo / starter kit

Agentic Index verified 2026-07-22

Alternatives to Anyshift

The closest documented capability profiles to Anyshift among SRE and DevOps agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.

  • Harness8.0 / 14A lighter documented profile than Anyshift
  • SRE.ai8.0 / 14A lighter documented profile than Anyshift
  • Metoro8.5 / 14Fuller documented coverage on Observability & Auditability
  • Phoebe7.5 / 14A lighter documented profile than Anyshift
  • Ciroos AI8.0 / 14Fuller documented coverage on APIs, SDKs & MCP Extensibility
  • Kura7.0 / 14A lighter documented profile than Anyshift

Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded

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