🏆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.

Sagy Blog

Practical guides for engineering teams investigating incidents, reducing MTTR, debugging embedded systems, and preserving reusable engineering memory.

How to Reduce MTTR Without Hiring More Engineers

MTTR usually grows because incident context is scattered. A repeatable investigation workflow helps teams move faster before headcount becomes the only answer.

Wissem

Wissem

Founder & CEO @ sagy

•
June 10, 2026
•
5 min read
How to Reduce MTTR Without Hiring More Engineers

A Practical Root Cause Analysis Workflow for Engineering Teams

Root cause analysis gets better when teams separate symptoms, evidence, hypotheses, validation, and memory instead of jumping straight to the first explanation.

Wissem

Wissem

Founder & CEO @ sagy

•
June 3, 2026
•
5 min read
A Practical Root Cause Analysis Workflow for Engineering Teams

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

Wissem

Founder & CEO @ sagy

•
May 29, 2026
•
4 min read
How to Investigate Incidents Across Slack, Jira, and GitHub

Engineers Lose Days, Sometimes Weeks, Just Reproducing a bug seen by a customer. Here's Why.

Before debugging even starts. After 18 years in embedded systems, the real time sink isn't debugging, it's everything that happens before it.

Wissem

Wissem

Founder & CEO @ sagy

•
May 22, 2026
•
6 min read
Engineers Lose Days, Sometimes Weeks, Just Reproducing a bug seen by a customer. Here's Why.

Customer Bug Investigation Workflow for Engineering Teams

Customer bugs move faster when support context, engineering evidence, reproduction steps, and final fixes stay connected.

Wissem

Wissem

Founder & CEO @ sagy

•
May 20, 2026
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5 min read
Customer Bug Investigation Workflow for Engineering Teams

How AI Agents Preserve Incident Knowledge for Engineering Teams

Incident knowledge disappears when it stays inside threads, tickets, and memory. AI agents can capture the investigation path while engineers work.

Wissem

Wissem

Founder & CEO @ sagy

•
May 13, 2026
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5 min read
How AI Agents Preserve Incident Knowledge for Engineering Teams

Why Static Knowledge Bases Like Confluence Are Failing Your Team (And What to Use Instead)

Static wikis weren't built for the speed of modern engineering. Here's why they break, and what an AI-native knowledge base looks like.

Wissem

Wissem

Founder @ sagy

•
April 27, 2026
•
7 min read
Why Static Knowledge Bases Like Confluence Are Failing Your Team (And What to Use Instead)

From One AI to Many: Why the Future Belongs to Purpose-Built Agents

The future isn’t a single “company chatbot”. The future is many agents, each with a clear job, creating clarity and trust.

Wissem

Wissem

Founder @ sagy

•
January 12, 2026
•
5 min read
From One AI to Many: Why the Future Belongs to Purpose-Built Agents

The Hidden Cost of Knowledge Silos in Software Teams

How information friction drains thousands of developer-hours each year, and how a living knowledge base like sagy fixes it.

Wissem

Wissem

CEO @ sagy

•
January 9, 2025
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4 min read
The Hidden Cost of Knowledge Silos in Software Teams

Stay Updated With Sagy

Get practical Sagy updates on incident investigation, root-cause workflows, and engineering memory.

We respect your inbox. Expect thoughtful updates, never spam.

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.

Schedule a demo
sagy

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

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