🏆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

Platform

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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HomeSee how Sagy helps engineering teams reduce investigation time.Incident Investigation AgentGather evidence across tools and surface the next action faster.Engineering MemoryPreserve decisions, fixes, and investigation paths automatically.Sagy in ActionFind the Sagy page that matches your team’s use case.

Solutions

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.

Workflows

Named workflows, not vague automation.

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.

Learn

Practical guides for engineering investigation.

Read focused content on MTTR, root-cause workflows, customer bugs, embedded reproduction, and secure AI agents for engineering teams.

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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.

Company

Company, hiring, and policy pages.

Learn who is building Sagy, how we handle data, and where we are hiring.

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TeamMeet the team building Sagy for engineering organizations.CareersExplore opportunities to help build the AI investigation layer.PrivacyUnderstand how Sagy handles customer information and product data.
Slack, Jira & GitHub workflow

Investigate incidents across Slack, Jira, and GitHub.

Most engineering incidents are not in one tool. Sagy follows the trail across conversations, tickets, code changes, docs, and prior decisions so engineers start with evidence instead of scattered tabs.

Schedule a demoIncident AgentIntegration hub
Pain
Workflow
Agent
Evidence
Human validation
Reusable memory

Start from the request

A Slack thread, Jira ticket, GitHub issue, or customer escalation becomes the investigation starting point. Sagy extracts symptoms, services, users, timestamps, and suspected systems.

  • Capture issue context from Slack or ticket text
  • Identify affected systems and linked identifiers
  • Route the request to the right investigation workflow

Cross-check code and tickets

The agent checks Jira history, GitHub commits, pull requests, linked docs, and prior incident memory to find previous fixes, recent regressions, and related work.

  • Find similar tickets and incidents
  • Inspect recent code changes around the affected area
  • Surface source links for human review

Summarize evidence for the owner

Instead of sending an engineer into scattered tabs, Sagy prepares a concise investigation packet with the likely path, source links, open questions, and a recommended next step.

  • Summarize the issue timeline
  • Call out missing context before escalation
  • Keep ownership and approval with the engineering team

Preserve the investigation

Once the engineer validates the answer, the path becomes reusable memory for future incidents across the same stack and connected tools.

  • Store evidence and final resolution
  • Improve the next root-cause workflow
  • Reduce repeated interruption of senior engineers

Keep exploring the Sagy investigation layer.

AI Incident Investigation AgentSlack, Jira & GitHub investigation articleRoot-cause workflow articleEngineering MemoryIntegrationsSecurity & Deployment

Ready to test Sagy?

Schedule a demo for your engineering investigation workflow.

Bring a real customer-reported hardware, firmware, or device issue. We will show how Sagy gathers context, runs the workflow, and preserves the investigation as reusable engineering memory.

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sagy

The AI investigation layer for engineering teams shipping software, firmware, hardware, and wireless systems.

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