🏆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

AI workflow agents that execute and learn.

Sagy helps teams map workflows, execute them with AI agents, and keep proven paths available for the next support issue, engineering investigation, or operational problem.

Schedule demo
HomeSee how Sagy helps teams execute and improve complex workflows.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.

Use Cases

Start with the use case, not the label.

Start with a service investigation if needed, then move into sales and support, embedded systems, or production workflows once the right agent opportunities are clear.

Schedule demo

Services First

Investigation ServicesWork with Sagy to investigate your current issues first, then decide which workflows should become agents.

Sales & Support

Incident Investigation AgentExample use case for turning inbound issues into structured investigations.Investigator DemoExample walkthrough of a support or escalation workflow.

Embedded Systems & Devices

Firmware ReproductionExample use case for reducing setup time before embedded debugging starts.Hardware Investigation AgentExample use case for device, lab, and embedded investigation workflows.Wireless Networking AgentExample use case for networking devices and field debugging workflows.

Production & Regulated Operations

Production Line Support AgentSimple use case for troubleshooting production lines with access to procedures, support context, and prior incidents.TelecommunicationsExample use case for production networking and connected-device operations.Avionics & AerospaceExample use case for safety-critical embedded and certification-heavy workflows.Medical DevicesExample use case for regulated device investigation and documentation workflows.

Workflow Foundations

Tool IntegrationsSee the tool layer that supports Sagy use cases.Confluence AlternativeExample of how Sagy can keep workflow knowledge alive without stale wiki pages.

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.

Schedule demo
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.

Schedule demo
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
•
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
•
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
•
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 one of your high-value workflows.

Bring a real support issue, engineering investigation, or production problem. We can start by helping investigate it as a service, then map the workflow and turn what works into reusable operational knowledge and agents.

Schedule a demo
sagy

AI workflow agents for teams running complex support, engineering, and operations work.

HomeIncident AgentSlack/Jira/GitHub WorkflowFirmware Bug ReproductionHardware AgentWireless AgentTelecommunicationsAvionicsMedical DevicesEngineering MemoryConfluence AlternativeIntegrationsSecurity & DeploymentBlogTeamCareersLinkedIn Contact
Contact

© 2026 Sagy. All rights reserved.