Building your own DIY agent for incident resolution?

→

Building your own DIY agent for incident resolution?

→

Understand what to look out for.

Building your own DIY agent for incident resolution?

→

Understand what to look out for.

Hyground vs

Resolve AI

Hyground vs Dash0

Hyground vs Resolve AI: the investigation runs where your data already is

Resolve AI is a US-hosted AI production engineer. You run a satellite in your own cluster. It proxies queries and redacts what it forwards, then sends the result to Resolve's cloud, where the agents do the reasoning. Hyground puts the agents themselves in your cluster, so the investigation happens next to the data rather than across a network boundary.

A fair starting point

No competitor comes closer to what Hyground does than Resolve AI. It investigates across code, infrastructure and telemetry as well, and stitches what it finds into causal timelines. It is careful about writes, too, and its documentation is explicit about how: the model never touches a write API, and a separate engine executes only after a human approves. It integrates first-party with the commercial observability vendors, Datadog, Splunk, Dynatrace and New Relic among them, where Hyground reaches those through custom MCP servers and keeps its first-party connectors for the open-source stack. It can also open pull requests, which Hyground cannot. Where the two part company is topology. Resolve's satellite is a proxy. The reasoning, and the summaries it keeps, sit in Resolve's cloud. Hyground arrives as a Helm install inside your own cluster, and the only traffic that leaves is the call to the model provider you picked.

Side by side

Hyground vs

Resolve AI

at a glance

What matters

Hyground

Resolve AI

Where the platform runs

Entirely in your own Kubernetes cluster, on-premises and air-gapped included.

A cloud-hosted SaaS, with a satellite you run in your cluster to reach local telemetry. The agents run in Resolve's cloud.

What leaves your network

Only calls to the model provider you choose. No telemetry, no usage tracking, no phone-home.

Queries are proxied and redacted by the satellite, then sent to Resolve's cloud. Raw telemetry is queried live and not retained; summaries and metadata are cached there.

LLM choice

Any provider through LiteLLM: a cloud model in your own tenant, a self-hosted model, or any OpenAI-compatible API.

Resolve operates the models. Their documentation describes no way to choose, swap or self-host one.

Observability integrations

First-party for the open-source stack: Prometheus, Loki, Elasticsearch, OpenSearch, Jaeger and InfluxDB. Commercial tools connect through custom MCP servers.

First-party for Datadog, Splunk, Dynatrace, New Relic, Grafana, Honeycomb, Chronosphere and more, queried from their cloud or proxied by the satellite.

Code changes

Hyground reads GitHub and GitLab and does not write to them. It recommends the fix; a person makes it.

Proposes a pull request with a suggested fix, created only after a human approves, then reviewed and merged as normal.

Your documentation and runbooks

Confluence Cloud and on-premises, up to 100 Git repositories, Artifactory and uploaded files, embedded in a vector store inside your cluster.

Confluence through the Atlassian connector, Slack and Teams channels, Glean, and a Resolve.md the team maintains. The index lives in Resolve's cloud.

Vendor and jurisdiction

Hyground GmbH, registered in Hamburg. It runs no control plane and has no operator path into your deployment.

Resolve AI, US-hosted. Their documentation gives one US address to allowlist for inbound access and describes no EU region.

Pricing model

Priced on infrastructure size, not seats. Quote on request.

Credits, metered per chat, task, triage, investigation and incident, against a contracted allowance, with a monthly cap on automated work.

Swipe to compare

Why teams choose Hyground

Where Hyground differs

The agents run in your cluster, not next to it

Hyground installs by Helm into your own Kubernetes cluster, and the reasoning happens there: the agents, the knowledge base, the audit trail, and the connection to your model. Resolve's satellite is a proxy. It scrapes Kubernetes APIs, queries your local observability tools and redacts what it forwards, but the agents that reason over the result run in Resolve's cloud, and the summaries they keep are stored there.

Any model, including one you host yourself

Hyground connects to any LLM provider through LiteLLM: a cloud model in your own tenant, a self-hosted model, or any OpenAI-compatible endpoint, with automatic fallback across a model list. Resolve operates its own models, and its documentation describes no way for a customer to choose, swap or self-host one.

Your runbooks are indexed inside the cluster

Hyground ingests Confluence, Cloud and on-premises, up to 100 Git repositories, Artifactory and uploaded files, and embeds them in a vector store that never leaves your cluster. Resolve reads Confluence, Slack, Teams and Glean, and holds what it learns in its own cloud, which is also where it stays when you leave.

No infrastructure mutation at all

Both products are read-only by default and require a human to approve anything else, and Resolve is explicit that its model cannot call a write API directly. The difference is the size of the write surface. Resolve can silence an alert or open a pull request once approved. Hyground does not restart, scale or reconfigure anything at all: adapters verify read-only at startup, below the model, and the only writes that exist are ticket comments and email.

One interface across every cluster

A central manager orchestrates workers in each cluster, with routing to a named cluster, parallel fan-out across all of them, and credentials that stay in the cluster they belong to. Resolve's satellite is configured per environment and scales by replica, but the correlation happens after the data reaches their cloud.

A German vendor with nothing of yours to lose

Hyground GmbH is registered in Hamburg and runs no SaaS control plane, no central key and no shared infrastructure, and has no operator access into your deployment. That is an architectural fact rather than a policy promise: there is no copy of your data on our side for anyone to ask us for. Resolve AI is US-hosted and its documentation describes no EU region.

Decision

When each platform fits

Resolve AI and Hyground investigate the same way and diverge on where the work happens. The decision is usually made by what your security review will accept, and by which observability tools you already run.

Choose Hyground when

Your telemetry is not allowed off your network. You need to pick the model that reasons over it, or host that model yourself. You run the open-source observability stack, or you operate on-premises and air-gapped sites where a SaaS control plane is not on the table.

Choose

Resolve AI

when

A US-hosted control plane passes your security review. You run commercial observability tools like Datadog or Splunk and want them supported first-party. And you want an agent that proposes the code fix itself, as a pull request.