Launching today
NeatContext
Give AI the context it needs during incidents
2 followers
Give AI the context it needs during incidents
2 followers
NeatContext is a local-first desktop app that gives AI the team-specific context it needs during incidents. Organize runbooks, logs, architecture notes, and troubleshooting guides, then use them with your preferred LLM while controlling what is shared. It aims to solve the accuracy issue caused by missing domain knowledge when using AI to handle incidents.
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Hi Product Hunt 👋
Today, we’re launching NeatContext.
We created NeatContext because we believe AI can meaningfully improve how engineering teams respond to incidents—but only when it has the right context.
LLMs can summarize logs, explain alerts, suggest investigation steps, and connect scattered information. But a general-purpose model does not understand your services, architecture, deployment history, runbooks, previous incidents, team conventions, or known failure patterns.
Without that domain knowledge, AI often produces answers that sound reasonable but are too generic—or simply wrong for your environment.
The same incident can also require completely different responses from different teams. A high error rate might lead one team to inspect a recent deployment, while another team needs to investigate a downstream dependency. A particular alert may be actionable for one service but considered noise for another.
Useful incident guidance must reflect the specific team, service, environment, and current situation.
That is the problem NeatContext is designed to solve.
NeatContext is a local-first desktop app that helps you organize and bring your operational knowledge to AI. You can use runbooks, troubleshooting guides, architecture notes, logs, previous incident records, local files, and other relevant context when investigating an incident.
We also found that operational knowledge rarely lives in one centralized location. It may be spread across Git repositories, internal documentation systems, incident platforms, work-item trackers, local files, spreadsheets, dashboards, or custom internal tools.
We do not believe teams should have to migrate and continuously maintain all of that knowledge inside another centralized platform just to make AI useful.
Instead, NeatContext is designed to work with the systems teams already use. Through extensions, teams can connect public tools, internal platforms, knowledge bases, incident systems, or service-specific APIs.
You remain in control:
• You choose what knowledge to include.
• You choose which systems to connect.
• You choose which LLM endpoint to use.
• You choose where your operational context is sent.
You can use a public LLM endpoint, a company-approved AI gateway, or a local model, depending on your organization’s requirements.
NeatContext is not trying to replace your incident-management platform, knowledge base, or internal systems. It is a lightweight context layer that helps the AI tools you already use understand your operational environment.
Because it is a desktop app, there is no heavy platform deployment or company-wide data migration required. You can install it, point it to the knowledge you care about, and start experimenting.
We’re still early, and we would especially value feedback from SREs, DevOps engineers, platform engineers, and anyone involved in on-call or incident response.
We would love to hear:
• What context is AI usually missing during your incidents?
• Where does your operational knowledge live today?
• Which systems should NeatContext connect to?
• What security and control requirements would your team have?
Thank you for checking out NeatContext. We’d love to hear your honest feedback and learn how you currently use—or avoid using—AI during incidents.
To thank the Product Hunt community, we’re offering NeatContext Plus free through December 31, 2026.
To claim it:
Create a NeatContext account.
Email support@neatcontext.com from the same email address with the subject Product Hunt Launch Offer.
We’ll manually activate Plus for your account.
No payment method is required. This offer is available to Product Hunt users who request it by July 31, 2026.