Agentic Index
Causely vs Resolve AI (2026)
Causely last verified ·Resolve AI last verified
Causely and Resolve AI both find what broke in production, by different methods. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Causely infers root cause and blast radius from a causal model of the environment, for SRE teams and their own AI agents through an MCP server and a GraphQL API, at $2,000 a month for up to 500 services, with a 30 day trial. Resolve goes on call with a team of specialized agents that triage alerts and investigate incidents in parallel, with actions waiting for approval by default, on credit metered contracts through sales. Choose Causely for causal analysis at a published price, and Resolve for a team of agents working an incident in parallel.
On the Agentic Index production ops ranking, Resolve AI clears the bar and Causely does not. Resolve AI documents all five resolution loop capabilities in full; Causely does not document workflow orchestration in full. 15 of the 38 vendors in the lane clear it. See the production ops ranking
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Causely and Resolve AI are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 1,084 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose Causely if
- Root cause should come from a causal model of your environment.
- Your own agents should query root cause through an MCP server or GraphQL.
- You want a published price and a 30 day trial.
Choose Resolve AI if
- A team of specialized agents should work an incident in parallel.
- Specialized agents should triage and investigate in parallel.
- Actions should wait for a person's approval by default.
| Feature | C Causely |
R Resolve AI |
|---|---|---|
| Action & orchestration | ||
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Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
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CauselyIntegrations & Tool Calling Telemetry comes from a named catalog of 20+ sources (Datadog, Dynatrace, Prometheus, Splunk, Elasticsearch, AWS, Azure, GCP, Kubernetes, Snowflake), and outbound workflows reach Slack, Microsoft Teams, incident.io, Splunk On-Call and a generic webhook. The executor on the in-cluster mediator applies scaling actions in the customer's cluster. Sourcedocs.causely.airead 2026-09-29 |
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Resolve AIIntegrations & Tool Calling 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 |
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Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
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CauselyWorkflow Orchestration A causal reasoning engine produces root cause and blast radius in one analysis, and there is no stated multi step workflow builder or multi agent runtime. The six MCP skills sequence tool calls inside the customer's own agent, so that orchestration belongs to the agent, not to Causely. Sourcedocs.causely.ai/agent-integration/mcp-serverread 2026-09-29 |
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Resolve AIWorkflow Orchestration 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 |
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Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
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CauselyTriggers & Channel Coverage Analysis runs continuously on streaming telemetry and on alerts routed in from existing tools ('An alert fires, Causely answers why'), and diagnoses are pushed to Slack, Teams, incident.io, Splunk On-Call or a webhook with nobody typing. Sourcedocs.causely.airead 2026-09-29 |
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Resolve AITriggers & Channel Coverage 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 |
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| Knowledge & context | ||
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Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
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CauselyKnowledge Grounding & RAG Causely maintains a causal model of the customer's environment. The mediator discovers services, infrastructure and dependencies, and agents periodically forward topology and symptom data to the backend, which keeps the causal graph current and queryable. Sourcedocs.causely.ai/getting-started/architectureread 2026-09-29 |
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Resolve AIKnowledge Grounding & RAG 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 |
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Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
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CauselyMemory & State Persistence What persists is application data, not agent memory. Diagnosis history is kept under 30 day retention, and thresholds, service tiers, custom causes and snoozed issues are settings the product applies. The causal model is the product's picture of the environment, and there is no stated separate memory layer. Sourcedocs.causely.ai/getting-started/architectureread 2026-09-29 |
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Resolve AIMemory & State Persistence 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 |
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| Control & trust | ||
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Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
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CauselyHuman Oversight & Guardrails Remediation commits only when a person triggers it from the UI, either as automated remediation or as a guided fix applied with one click, and automated actions require the executor to be enabled on the mediator in that cluster. There is no stated way for remediation to run without a person. Sourcedocs.causely.ai/in-action/automate-remediationread 2026-09-29 |
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Resolve AIHuman Oversight & Guardrails 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 |
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Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
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CauselySecurity, Identity & Governance Access is managed through workspace SSO, user management with assigned roles, personal and tenant wide API tokens, and MCP configuration tools limited to Developer and Admin roles, backed by an admin audit log. Causely holds SOC 2, with the report available on request, and encrypts data in transit and at rest. Sourcecausely.ai/securityread 2026-09-29 |
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Resolve AISecurity, Identity & Governance 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 |
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Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
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CauselyObservability & Auditability Each diagnosis carries its causal chain and the targeted telemetry sent as evidence, and remediation keeps an auditable action history tied to the entity it changed, a per action record readable after the fact. Sourcedocs.causely.ai/in-action/automate-remediationread 2026-09-29 |
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Resolve AIObservability & Auditability 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 |
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Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
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CauselyDeployment & Data Residency The mediator and agents always run in the customer environment, the causal engine runs in the customer's cloud (BYOC) or in Causely managed infrastructure, and Enterprise offers on premises and air gapped deployment. Raw telemetry stays local. Causely publishes no region list. Sourcedocs.causely.ai/getting-started/architectureread 2026-09-29 |
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Resolve AIDeployment & Data Residency 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 |
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| Solution readiness | ||
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Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
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CauselyPrebuilt Agents, Templates & Packs Six named skills ship with the MCP server, each with a distinct job. Three handle live incidents (causely-alert-triage, causely-correlated-incidents and causely-k8s-investigation), and the other three cover change impact (causely-change-impact), health reporting (causely-health-reporting) and postmortems (causely-postmortem). Sourcedocs.causely.ai/agent-integration/mcp-serverread 2026-09-29 |
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Resolve AIPrebuilt Agents, Templates & Packs 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 |
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| Platform extensibility | ||
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Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
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CauselyModel Flexibility & Routing Diagnosis comes from a deterministic causal reasoning engine, with no stated LLM provider or customer model choice. Customers can bring their own agent through the MCP server, which extends the product and is not a choice of model. Sourcecausely.airead 2026-09-29 |
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Resolve AIModel Flexibility & Routing 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 |
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APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
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CauselyAPIs, SDKs & MCP Extensibility A GraphQL API at api.causely.app/query takes bearer token authentication with personal and tenant API tokens, and comes with query guides for defects and root causes, hiding root causes, and SLOs on paths. An MCP server at api.causely.app/mcp adds 45 tools, including configuration of thresholds, service tiers and snoozing. Sourcedocs.causely.ai/api/graphql-clientsread 2026-09-29 |
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Resolve AIAPIs, SDKs & MCP Extensibility 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 |
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Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
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CauselyTesting, Debugging & Optimization There is no stated evaluation harness, scored tests or quality gate for the diagnosis engine. Post deploy validation compares the customer's services before and after a release, which tests the customer's change and not the agent, and the 63 percent benchmark is Causely's own marketing figure. Sourcedocs.causely.ai/agent-integration/mcp-serverread 2026-09-29 |
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Resolve AITesting, Debugging & Optimization 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 |
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| Specialist automation | ||
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Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
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CauselyBrowser & Computer Use Causely works through telemetry sources, the in-cluster executor, a GraphQL API and an MCP server, with no stated browser, desktop or computer control. Sourcedocs.causely.airead 2026-09-29 |
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Resolve AIBrowser & Computer Use 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 |
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Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | C Causely |
R Resolve AI |
|---|---|---|
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Entry price Lowest public entry point |
Professional at $2,000 per month for up to 500 services. Enterprise is custom. | Contact sales. Contracts are metered in credits, and no rates are published. |
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Pricing confidence How public the numbers are |
Public, exact | Contact only |
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Billing Primary billing axis |
Billed monthly by service count on Professional, up to 500 services. Enterprise runs on a custom plan. | Credits per unit of work, consumed by chats and tasks, investigations, incidents and triages. The credit cost of each is defined in the contract. |
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Variable cost Workload / overage exposure |
Low variable cost | Medium variable cost |
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Free tier / trial Try before you buy |
No free tierTrial
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No free tierTrial
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Buying motion Self-serve vs sales call |
Mixed | Sales call |
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Pricing verified When this pricing was last checked |
Product updates
Newest first, each linked to its source.
Causely
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· MCP / tool calling / API
The hosted Causely MCP server now carries its own guidance on how to use its tools, so a new background agent works well from its first connection.
Source -
· MCP / tool calling / API
The get_diagnosis_details and get_issue_details MCP tools in Causely now return the causality chain behind a diagnosis, listing each affected entity, its distance from the root entity, and the symptoms, events and SLOs the diagnosis causes there.
Source
Causely publishes its Professional price, and Resolve AI sells credit metered contracts through sales.
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