🏆Finalist, Belgium Startup Awards 2026·Backed by Start it @KBC Accelerator
🏆Finalist, Belgium Startup Awards 2026·Backed by Start it @KBC Accelerator
🏆Finalist, Belgium Startup Awards 2026·Backed by Start it @KBC Accelerator
🏆Finalist, Belgium Startup Awards 2026·Backed by Start it @KBC Accelerator
Sagy

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The AI investigation layer for engineering teams.

Sagy helps software, firmware, and hardware teams investigate incidents faster, reduce repeated context hunting, and keep proven fixes available for the next issue.

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Focused pages for each engineering investigation problem.

Whether your team ships software, firmware, hardware, or connected devices, Sagy helps recover context and turn investigations into reusable workflows.

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Software Incident AgentInvestigate production issues across tickets, code, logs, and docs.Hardware & Embedded AgentInvestigate customer-reported device issues with firmware, serial, SSH, and lab context.Wireless & Networking AgentInvestigate WiFi, Bluetooth, Zigbee, Matter, and networking failures.Engineering MemoryMake every resolved incident easier to investigate next time.Onboarding AgentsHelp new engineers learn from your team’s real decisions and workflows.

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Sagy follows the exact operational workflows your engineers repeat today, then improves them with every validated investigation.

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Slack, Jira & GitHubConnect the conversation, ticket history, and code changes behind an issue.Firmware ReproductionSpend less time rebuilding setups before embedded debugging starts.Tool IntegrationsConnect the tools where incidents, code, docs, logs, and decisions already live.Confluence AlternativeKeep engineering knowledge alive without relying on stale wiki pages.Investigator DemoWatch how Sagy turns an inbound issue into a structured investigation.

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Security & DeploymentReview private deployment, human approval, auditability, and access control.Blog IndexRead practical articles for engineering teams investigating complex issues.Reduce MTTRLearn how repeatable incident investigation lowers resolution time.Root-Cause WorkflowFollow a source-backed workflow for engineering root-cause analysis.Slack Jira GitHub IncidentsConnect conversations, tickets, and code changes during incidents.Customer Bug WorkflowTurn customer reports into structured engineering investigations.Incident KnowledgeSee how AI agents preserve fixes, evidence, and decisions.Embedded Bug ReproductionLearn why reproducing customer bugs can take days before debugging begins.Static Knowledge BasesSee why static docs miss the decisions engineers need during incidents.Purpose-Built AgentsUnderstand why focused agents outperform generic assistants for engineering work.

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Home/Blog

How to Investigate Incidents Across Slack, Jira, and GitHub

Modern incidents rarely live in one system. This workflow connects the conversation, ticket, code change, and prior decision trail.

Wissem
WissemFounder & CEO @ sagy
May 29, 2026
4 min read
How to Investigate Incidents Across Slack, Jira, and GitHub

A modern engineering incident is a trail. The customer complaint may start in Slack. The owner may be assigned in Jira. The regression may sit in a GitHub pull request. The fix may depend on a decision buried in docs.

If those pieces stay disconnected, investigation time grows. The goal is to turn Slack, Jira, and GitHub into one evidence path.

Start From The Conversation

Slack and Teams threads are often the first place symptoms appear. They include timestamps, affected users, screenshots, guesses, and questions that never make it into the ticket.

Sagy extracts the useful pieces and uses them to search for linked Jira tickets, related incidents, and code areas.

Use Jira For History And Ownership

Jira gives structure: status, assignee, priority, duplicates, affected versions, and previous fixes. It also reveals whether the same issue has appeared before.

A good workflow checks similar tickets before asking a senior engineer to remember them manually.

Use GitHub For Change Context

GitHub shows what changed:

  • recent commits touching the affected area
  • pull requests linked to the ticket
  • owners and reviewers who know the code path
  • tests or workflows that changed around the same time

Sagy connects those changes back to the original symptoms so engineers can validate the likely root cause faster.

Make The Investigation Reusable

The workflow should end with reusable memory: what happened, what evidence mattered, what fix worked, and which links support the conclusion.

For teams that want this workflow as a focused product page, see the Slack Jira GitHub incident investigation agent.

Related Sagy pages

Slack, Jira & GitHub WorkflowSee the focused Sagy workflow for connected incident investigation.IntegrationsReview the tools Sagy connects to during engineering investigations.
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The AI investigation layer for engineering teams shipping software, firmware, hardware, and wireless systems.

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