Resolve AI vs Wild Moose (2026)

An integration catalog of about 40 systems covers AWS, GCP, Azure, Datadog, Dynatrace, Splunk, Grafana, New Relic, PagerDuty, ServiceNow, Sentry, Snowflake, GitHub, Atlassian, Slack and Microsoft Teams, plus any connected MCP server. On approval the agent creates silences, downtimes or mutes in Grafana, Datadog, AlertManager, Kloudfuse and Sumo Logic, opens fix pull requests and dispatches GitHub Actions workflows.

SourceResolve docs llms.txt index, Mitigation Actions and Security and Administration; docs.resolve.ai/mitigation-actionsread 2026-10-22

Wild Moose connects observability tools, code repos, CI/CD pipelines and internal tools, but all integrations run strictly read only. Its agents read outside systems and report to Slack or Teams, and do not act in them. Named integrations span alerting (PagerDuty, Incident.io, Squadcast, OpsGenie, FireHydrant), observability and data (Grafana, Datadog, New Relic, Sumo Logic, Coralogix, Prometheus, Loki, Tempo, Zabbix, Snowflake, ClickHouse, Trino) and knowledge bases (Jira, Fibery, Zendesk, Confluence, Notion).

SourceWild Moose, wildmoose.ai/security and /integrationsread 2026-10-05

A team of domain-specialized agents investigates in parallel, pursuing hypotheses that engineers can redirect, and verifies findings against production evidence, with a dedicated reviewer validating them. Custom agents compose Resolve's MCP, API and skills into the customer's workflows, and Temporal connects orchestration platforms.

Sourceresolve.ai/product/incidentsread 2026-10-22

Micro-agents specific to each company work as a coordinated system, running investigations in parallel, and are built and managed as code. A customer describes a check, tests it and iterates on it. Triage agents start each investigation, and specialized agents deploy based on the signals they find.

SourceWild Moose, wildmoose.ai/productread 2026-10-05

The On-call Agent goes on call on the customer's behalf, holding the pager and triaging alerts. Alerts arrive by PagerDuty, Splunk On-Call and alert webhooks from any source. Tasks run on a schedule or cron, when a matching message appears in a watched Slack or Microsoft Teams channel, or on demand, and the Teams app investigates alerts posted to alert channels.

Sourcedocs.resolve.ai/tasksread 2026-10-22

When an alert fires, Wild Moose activates triage agents to run checks, pull evidence and narrow down the most likely root cause. Alerts come from PagerDuty, Incident.io, Squadcast, OpsGenie and FireHydrant, and alert enrichment takes under a minute.

SourceWild Moose, wildmoose.ai/product, /integrations and wildmoose.airead 2026-10-05

Team Knowledge is a maintained store of runbooks, docs, dashboard guidance and skills at organization, team and personal level that Resolve activates dynamically during investigations, examining all knowledge tied to the alert and its owning teams. Skills follow the open Agent Skills format and load on demand, and Hivemind adds production state awareness across alerts and incidents.

Sourcedocs.resolve.ai/team-knowledgeread 2026-10-22

Each investigation gathers logs, metrics, traces and code from the connected tools at alert time, processed in memory and discarded afterward. Wild Moose says it learns the customer's infrastructure and ingests historical incident data to understand the environment, and it connects knowledge bases such as Jira, Confluence, Notion, Zendesk and Fibery. It names no index, graph or knowledge store it maintains.

SourceWild Moose, wildmoose.ai, /product and /integrationsread 2026-10-05

The agent keeps learnings it has accumulated, which its tasks can read, and proposes new runbooks and edits to team docs from a conversation or by reviewing completed investigations for lessons. Resolve does not say how those learnings are stored, reviewed or deleted, and Team Knowledge itself is written by people.

Sourcedocs.resolve.ai/tasksread 2026-10-22

Gaps an investigation finds become new or updated micro-agents committed as a pull request. These are procedures the product runs, and Wild Moose names no memory the agents read. Processing is ephemeral with no data retention, and when Wild Moose says it learns from each incident, that learning is this update loop. Wild Moose stores no logs, metrics or other raw data.

SourceWild Moose, wildmoose.ai/product and /securityread 2026-10-05

Alert silences and fix pull requests run only after a person approves them in the Resolve UI or Slack. GitHub Actions workflow tools, in preview, also default to approval, and an admin can let an individual tool run on its own. The model that proposes actions never calls write APIs, which a separate engine executes, and write permissions are enabled per integration.

Sourcedocs.resolve.ai/security-and-administrationread 2026-10-22

Integrations are strictly read only, and the agents suggest fixes for engineers to carry out, so action stays with people. Agent changes arrive as pull requests validated against past incidents and gated by the customer's code host. Wild Moose names no approval step inside the product.

SourceWild Moose, wildmoose.ai/product and /securityread 2026-10-05

Customers get SSO (Google, Okta, Azure AD), SCIM directory sync with sign in enforcement, RBAC, access limited to roles, environments or namespaces, and audit logs. Compliance covers SOC 2 Type II, GDPR and HIPAA, backed by a trust center.

SourceResolve security page and docs llms.txt index (Security and Administration pages); resolve.ai/securityread 2026-10-22

The company says it is SOC 2 Type II certified and adheres to SOC 2 standards for security, availability and confidentiality, with end to end encryption, no data retention and no training on customer data. Wild Moose names no SSO, roles or permissions model.

SourceWild Moose, wildmoose.ai/securityread 2026-10-05

Each investigation shows an Evidence Trail with timestamps and verification and a Workbench of what each agent is doing. An Activity Dashboard records every action, including who proposed it, who approved or rejected it, when, and what was affected.

Sourcedocs.resolve.ai/mitigation-actionsread 2026-10-22

Every investigation step is visible, from the data sources queried to findings, AI reasoning and recommendations, beside a structured root cause analysis with key signals, ranked hypotheses and next steps. Each run keeps a record of what the agents queried.

SourceWild Moose, wildmoose.ai/productread 2026-10-05

Customers choose between a shared multi tenant cloud and a dedicated single tenant cloud deployment with bring your own keys. The Satellite agent runs in the customer's Kubernetes or ECS, keeps credentials local and proxies queries into Resolve's cloud. There is no region list or customer environment option.

Sourcedocs.resolve.ai/resolve-satelliteread 2026-10-22

With on prem support the customer can deploy Wild Moose within its own infrastructure and control where data is processed, and hosted processing runs in memory and is ephemeral, with no data retained outside the customer's network.

SourceWild Moose, wildmoose.ai/securityread 2026-10-05

Separately named agents ship for their own jobs, namely the On-call Agent that holds the pager and triages alerts, the Incident Resolution Agent for root cause and mitigation, and Issue Remediation for recurring problems. Background agents for operational tasks start from a template library that includes a deploy health monitor, a daily digest, an alert triager and a resource report.

Sourceresolve.ai/product/operational-tasksread 2026-10-22

Micro-agents are checks specific to each company, built and managed as code for each customer, and the customer assembles them. Wild Moose publishes no prebuilt agents or templates. When an alert fires, triage agents run first and specialized agents follow based on what they find.

SourceWild Moose, wildmoose.ai/productread 2026-10-05

Resolve uses frontier LLM models combined with domain-specific models, without naming a provider, and customers cannot choose a model.

Sourceresolve.airead 2026-10-22

Wild Moose names neither a model provider nor any customer model choice. It does not fine tune or train AI models on customer data.

SourceWild Moose, wildmoose.ai/securityread 2026-10-05

A REST API at app0.resolve.ai with bearer personal or organization tokens triggers, lists and reads investigations, alongside a Resolve MCP server, plugins for Claude Code, Codex and Cursor, and skills in the open Agent Skills format.

Sourcedocs.resolve.ai/resolve-rest-apiread 2026-10-22

There is no published API, SDK or MCP server for driving Wild Moose, and there are no docs or developer pages. Customers manage micro-agents as code, but these are their own checks and do not drive the platform. Results reach teams in Slack or Microsoft Teams.

SourceWild Moose, wildmoose.ai/product and /integrationsread 2026-10-05

A change can be evaluated against an earlier result. After updating knowledge or integrations, Reinvestigate alert re-runs the same alert so the new result can be compared against the original, and thumbs up or down verdicts on each report collect under Analytics, Feedback.

Sourcedocs.resolve.ai/tuning-accuracyread 2026-10-22

Micro-agents are tested against real past incidents. A customer describes a check, tests it against historical incidents and iterates until it performs reliably, and each new or updated agent is validated against past incidents before it runs in production. Wild Moose reports 90% accuracy within three weeks and, at Wix, root cause accuracy above 80%.

SourceWild Moose, wildmoose.ai/product and wildmoose.airead 2026-10-05

Work runs through integrations, a Satellite proxy, Slack, Microsoft Teams, a REST API and an MCP server, with no browser, desktop or computer control.

SourceResolve docs llms.txt index and Incidents page; resolve.ai/product/incidentsread 2026-10-22

Agents read connected tools through read only integrations. Wild Moose names no browser, desktop or computer control. Alerts arrive from tools such as PagerDuty and OpsGenie, and answers go to Slack or Teams.

SourceWild Moose, wildmoose.ai/product and /integrationsread 2026-10-05