I quit a job after 6 months because I didn’t want to be on call to fix whatever happened in the middle of the night.

I only had to do it twice, but that was it for me.

Back then, you had to start digging through logs, dashboards, and old conversations in the middle of the night, trying to figure out how to fix whatever was broken.

Hats off to those of you who do this every day without complaining.

That cold start is one of the hardest things about fixing a problem. Figuring out what’s happening takes most of your time.

I’m working with @incident_io, and their new agentic root-cause analysis product, Investigations, gives you a working hypothesis before you even start looking.

This makes a world of difference.

Here is the workflow:

1. It gathers context from telemetry, deployments, commit history, past incidents, Slack, documentation, and service dependencies.

2. It builds a structured hypothesis explaining what broke, why it broke, and where responders should look next.

3. It keeps analyzing new signals in the background while you ask questions or run parallel investigations.

Every hypothesis links to its sources, so you can inspect the evidence and decide what to do next.

And because it’s built on Nexus, a living model of your own systems and past incidents, it knows your setup rather than guessing at your logs as a generic LLM would.

So you go from having no clue what happened to a really useful starting point in seconds.

Check out this link: https://go.incident.io/0fNPXZ6

Thanks to the team for partnering with me on this post.

Investigations tackles the hardest part of the incident and gets you from alert to resolution an order of magnitude faster.

Source: https://incident.io/investigations?utm_source=x&utm_medium=social&utm_campaign=FY26-Q3-819-INFL-LP-investigations-LearnMore&utm_content=Santiago-Valdarrama&utm_term= Investigations

Agentic root cause analysis

Investigations tackles the hardest part of the incident and gets you from alert to resolution an order of magnitude faster.

A production harness for reliability agents

Investigations runs on a purpose-built harness that re-assesses as new signals land, builds findings from real evidence, and pressure-tests every hypothesis with an adversarial agent before it reaches you.

Respond at afundamentallydifferent speed

With our agent scanning through logs, code, and context, your team can move at a speed that manual debugging alone couldn’t match.

### Triage quicker than ever

Before investigating, understand the severity, impact area, and if escalation is needed or you can relax.

### Instant root cause analysis

When it’s serious, Investigations has already gathered context to show what broke and why, so you start with real evidence.

### Context-aware agent for debugging

Our agent works alongside you for the rest of the incident, running parallel analysis and surfacing things before you’ve thought to look.

Reduce the cost of incidents

The cost of an incident isn’t just the downtime. It’s everything around it: engineering hours, customer trust, and product velocity.

• Fewer people pulled in
• More time building
• Less customer impact

Works with every agent in your stack

Investigations can hand off seamlessly to the agents and tools you already use: a coding agent, a support tool, anything connected via MCP. Our goal is humans and agents in lockstep, all the way to resolution.

No more cold starts

The moment an incident is declared, Investigations has already done a first pass. Before anyone starts digging, you have a clear picture of what you’re dealing with and where to start.

You don’t have to debug alone

You get an agent with full context on your environment that works with you, answering questions and running parallel analysis, across the whole investigation.

Built on the power of Nexus

Investigations runs on Nexus, our production intelligence model. It reasons across your entire environment in real time, so at 3am it can make high-conviction hypotheses on a system it knows inside out.

Learn more about Nexus- Has access to every piece of relevant context your team has ever produced

• Reasons across telemetry, deployments, code, and incident history
• Uses an adversarial agent to challenge its own conclusions before sharing
• Gets smarter with every incident, the model learns which patterns repeat

Intelligencecompounds

Every incident teaches it something. The more you use it, the smarter it gets.

Trusted when it matters most

Built for your most critical moments, with the accuracy, transparency, and data isolation enterprise teams require. View our Vanta trust center

### Measurably accurate

We backtest against real historical incidents daily, and alert on any degradation before it reaches you.

### Evidence-backed audit trail

Every hypothesis links back to its sources and an investigation timeline lets you follow the agent’s reasoning from first signal to final conclusion.

### Your data stays yours

Every customer gets their own instance of Nexus, our production intelligence model, never shared with other customers.

### SOC 2 compliant

Code analysis runs in isolated, sandboxed containers torn down after use, and we redact sensitive data before it ever reaches a model.

### Zero data retention with model providers

We have agreements with our providers so they can’t store customer data for logging or training.

### Never takes action without you

The only change Investigations can make to your systems is a pull request you review and merge yourself.

So good, you’ll break things on purpose

Ready to put AI to work on your incidents? Book a call with our team today.