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Causely
New York, United States
What it is
Causely gives operations agents causal context from a live model of a system to help diagnose issues and act proactively. Its causal inference identifies upstream causes across cascading symptoms and is described as deterministic and explainable. Agents can traverse causal graphs to assess blast radius and compare system behavior before and after deployments; they connect to the model through MCP. Causely ingests traces, metrics, logs, and alerts from observability tools such as OpenTelemetry, Datadog, and Prometheus. Its supported technologies include 73 items across agents, telemetry sources, installation options, and workflow destinations including Slack and Microsoft Teams. Deployment options include Kubernetes, Docker, hybrid SaaS, and bring-your-own-cloud; BYOC can run the full application in a customer environment, including air-gapped deployments. Causely says raw source data stays in the customer environment while distilled symptom state is sent to its SaaS backend. Professional Edition costs $2,000 per month and includes up to 500 services, 30 days of data retention, and standard hybrid deployment. Causely was founded in 2022 and is based in New York.
For and against
For
- Identifies upstream causes across cascading symptoms
- Supports blast-radius and deployment-risk analysis
- Connects agents through MCP
- Offers BYOC, including air-gapped deployment
- Professional Edition includes up to 500 services
Against
- Professional Edition costs $2,000 per month
- No free plan is listed
- Professional data retention is 30 days
The verdict
Causely centers on supplying operational agents with causal system context rather than just telemetry inputs. The $2,000-per-month Professional Edition includes defined service and retention limits, while Enterprise pricing is custom.
Who it suits
Causely is aimed at teams building or running operations agents and SRE or platform teams responsible for reliability. Its deployment choices may suit organizations that need hybrid or private environments.
Plans and prices
Professional Edition
Up to 500 services · All published integrations · Dedicated Slack/Teams channel for ad-hoc help, best effort response times · 30 days data retention
Read 30 Sep 2026 · causely.ai
Enterprise Edition
No limit on included services · Custom integrations · Dedicated Slack/Teams channel with optional custom SLAs and Forward-Deployed Engineering support · Custom data retention
Read 30 Sep 2026 · causely.ai
On the record
- Agent access
- Agents connect to Causely’s causal model through MCP.causely.ai · read 30 Sep 2026
- Blast radius and deploy risk
- Agents can use causal graph traversal for blast radius analysis and compare system behavior before and after deployments.causely.ai · read 30 Sep 2026
- Company history
- The about page says founder Dr. Shmuel Kliger created Causely with former Turbonomic engineering leaders and experts in distributed systems and causal analysis.causely.ai · read 30 Sep 2026
- Company location
- The company site says it is made in New York and around the world.causely.ai · read 30 Sep 2026
- Data handling
- Causely says raw source data stays in the customer environment and only distilled symptom state is sent to its SaaS backend.causely.ai · read 30 Sep 2026
- Deployment
- The documentation lists Kubernetes, Docker, and other environments for deploying the mediator; the maker also describes hybrid SaaS and bring-your-own-cloud options.docs.causely.ai · read 30 Sep 2026
- Integrations
- The supported technologies page lists 73 technologies, including agents, telemetry sources, installation options, and workflow destinations such as Slack and Microsoft Teams.docs.causely.ai · read 30 Sep 2026
- Intended users
- Causely says it is for teams building or running operations agents and for SRE and platform teams responsible for reliability.causely.ai · read 30 Sep 2026
- Private deployment
- The BYOC option runs the entire application within the customer environment, including for air-gapped deployments.causely.ai · read 30 Sep 2026
- Purpose
- Causely gives operations agents causal context from a live model of a system so they can diagnose issues and act proactively.causely.ai · read 30 Sep 2026
- Root cause analysis
- Its causal inference identifies upstream causes across cascading symptoms and is described as deterministic and explainable.causely.ai · read 30 Sep 2026
- Security
- The security page states that transferred symptom data is encrypted in transit and at rest and says Causely adheres to SOC 2 standards.causely.ai · read 30 Sep 2026
- Support
- The Professional plan includes a dedicated Slack or Teams channel for ad-hoc help with best-effort response times.causely.ai · read 30 Sep 2026
- Telemetry inputs
- Causely ingests traces, metrics, logs, and alerts from existing observability tools, and its homepage names OpenTelemetry, Datadog, and Prometheus as examples.causely.ai · read 30 Sep 2026
