What is AI-powered incident management?

AI-powered incident management uses intelligent agents to automate incident response tasks like alert triage, runbook execution, root cause analysis, and team notifications. Instead of relying solely on on-call engineers, AI agents can handle initial diagnosis and remediation steps 24/7, reducing MTTR and on-call burnout.

Is Akmatori open source?

Yes, Akmatori is an Apache 2.0 open-source project. You can inspect the code, run it on your own infrastructure using Docker or Kubernetes, and keep complete control over your data and incident workflows.

What LLM providers does Akmatori support?

Akmatori supports multiple LLM providers including OpenAI (GPT-4), Anthropic (Claude), Google (Gemini), and OpenRouter. You can also use on-premise models like Mistral, GLM, Kimi, or Minimax for data sovereignty requirements.

How does Akmatori integrate with PagerDuty?

Akmatori integrates with PagerDuty via webhooks and the PagerDuty API. When an incident is triggered, Akmatori's AI agents can automatically acknowledge alerts, gather context from your observability stack, execute diagnostic runbooks, and post updates to incident channels.

Can Akmatori reduce on-call burnout?

Yes. Akmatori handles routine incidents autonomously, filters alert noise, and only escalates to human engineers when necessary. This significantly reduces the number of pages during off-hours and allows SRE teams to focus on high-impact work instead of repetitive troubleshooting.

What observability tools does Akmatori work with?

Akmatori ingests alerts from Prometheus Alertmanager, Grafana, Datadog, Zabbix, and PagerDuty, and can monitor Slack channels. AI agents reach your infrastructure through real tools such as SSH and Kubernetes to diagnose issues.

November 8, 2026

Akmatori vs Resolve.ai: Open-Source Self-Hosted or Enterprise SaaS?

Akmatori vs Resolve.ai: Self-Hosted vs SaaS AI SRE

Resolve.ai is one of the best-known names in the AI SRE category. It describes its product as an AI that goes on-call on your behalf, and its customer list includes Coinbase, DoorDash, Salesforce and MongoDB. Akmatori solves a similar problem, investigating alerts and finding root cause, with a different model: open source, self-hosted, and with your choice of LLM.

We build Akmatori, so this comparison has a point of view. Resolve.ai facts below come from resolve.ai and its public documentation as of November 2026. Where we could not verify something, we say so.

At a Glance

	Resolve.ai	Akmatori
License	Proprietary	Apache-2.0 open source
Deployment	Cloud SaaS, with an optional in-cluster "Satellite" agent	Self-hosted with Docker Compose; no SaaS
Where the investigation runs	Resolve's cloud	Your servers
Models	Resolve's own models plus frontier models chosen by Resolve	Your choice: OpenAI, Anthropic, Google, OpenRouter, NVIDIA NIM, MiniMax, or any OpenAI-compatible endpoint you host
Alert sources	Alertmanager, PagerDuty, Splunk On-Call, generic webhooks	Alertmanager, Grafana, PagerDuty, Datadog, Zabbix, Slack channels, cron jobs
Write actions	Read-only by default; silences, PRs and GitHub Actions behind approval	Read-only SSH by default; risky actions become proposals approved in UI or Slack
Interfaces	Slack, Microsoft Teams, web UI, API, MCP server	Web UI, Slack, API
Compliance	SOC 2 Type 2, HIPAA, GDPR	You run it, so it inherits your controls
Pricing	Credit-based, contact sales	Free; you pay for your own model usage

Where Resolve.ai Is Stronger

Enterprise readiness today. SOC 2 Type 2, HIPAA and GDPR, a documented security model, and a long list of large customers. If a procurement team needs a vendor with certifications and a support contract, Resolve.ai has them.

Integration depth. Resolve.ai connects to Datadog, Dynatrace, New Relic, Splunk, Chronosphere, Honeycomb, Elasticsearch, Sentry, ClickHouse, Snowflake, the three big clouds, GitHub, Atlassian and ServiceNow. Its approval model for write actions is careful: the docs say the model never has direct access to write APIs.

Resources. Resolve.ai raised a $125M Series A in February 2026 and an extension in April, and it runs its own research lab. That pays for a large team working on the product.

Where Akmatori Is Stronger

Your data stays in your network. Resolve.ai's Satellite keeps credentials behind your firewall and proxies queries, but the investigation itself runs in Resolve's cloud. We did not find a fully on-premises or air-gapped option. Akmatori runs entirely on your servers. With a self-hosted model, no incident data leaves your network at all.

You choose the model. Resolve.ai does not name the models it uses, and we found no way to bring your own. Akmatori works with any major provider or with a model you host. You can measure the choice: SRE Bench runs 12 real incidents on a fresh Akmatori install per model and publishes root-cause accuracy and cost per solved incident.

Cost you can predict. Akmatori is free. Your cost is your own model usage. In the August 2026 SRE Bench edition, several models found the root cause in all 12 incidents for less than $0.10 per solved incident. Resolve.ai pricing is credit-based and not public.

Infrastructure outside the big SaaS stack. Akmatori has first-class Zabbix, NetBox, VictoriaMetrics and read-only SSH tools. Zabbix is not in Resolve.ai's integration list. For teams with many Linux servers and classic monitoring, that matters.

Open code. You can read what the agent does, audit the tools it can call, and change them. When a security review asks what exactly the AI can run on production hosts, the answer is in the source.

How to Choose

Choose Resolve.ai if:

You are a large company that buys SaaS with certifications, SLAs and a vendor team behind it.
Your observability stack is mostly commercial SaaS: Datadog, Splunk, New Relic, Dynatrace.
You prefer a managed service to running another system.

Choose Akmatori if:

Incident data, logs and credentials must stay inside your network, or you are in a regulated or sovereign environment.
You want to pick, measure and change the model, including models you host yourself.
You run Prometheus, Grafana, Zabbix or VictoriaMetrics on your own servers.
You want to start today without a sales process.

Conclusion

Resolve.ai and Akmatori aim at the same problem from opposite ends. Resolve.ai is a well-funded enterprise SaaS with deep commercial integrations. Akmatori is an open-source agent you run and control yourself, with your own model and your own data boundary. If self-hosting is a requirement, see self-hosted AI SRE with local models, or connect your first alert source with the Alertmanager guide.

If your team wants AI-assisted incident workflows on your own infrastructure, Akmatori helps SRE teams investigate alerts, coordinate response, and automate safe infrastructure actions. Powered by Gcore for global infrastructure reliability.

Akmatori team