
AI agents for engineering teams
that execute end-to-end workflows.
Sagy gives engineering teams AI agents that investigate issues, reproduce them on the embedded systems, and fix them. Agents learning from every execution.
Built with engineering teams who feel this pain every day.
Automated incident investigation across your tools.
Each Sagy agent gathers context from tickets, logs, code, and runbooks, then executes your investigation workflow to help engineers identify root causes and reduce mean time to resolution (MTTR).

Support Agent
Analyzes each customer request to identify bugs, issues, and the right next step.
Slack
reads threads
Linear
checks issues
GitHub
reviews PRs
Docs
reads runbooks
Jira
opens tickets
- Loaded issue
- Loaded customer context from database
- Loaded system logs from server
- Loaded Jira tickets
- Bug identified
- Matched similar ticket: #3400
- Fix in progress
- Prepared draft reply for customer
Engineering knowledge management that takes action.
Turn investigation playbooks, firmware procedures, and team knowledge into reusable workflows your agents can execute and refine.
Discover
Find the right workflow
Refine
Keep workflows accurate
Execute
Run with your team or AI agents

Engineering context across Jira, Slack, and GitHub.
Connect Jira, Slack, GitHub, Confluence, SharePoint, and Microsoft Teams so AI agents can investigate issues with the engineering context already held across your tools.
Incident investigation across software, firmware, and devices.
Sagy follows the same operating model on every page: pain, workflow, agent, evidence, human validation, and reusable engineering memory.

Problem
Client Alpha reports intermittent boot failures on device X2000 after release 3.1.2. Please investigate the issue.
Context from
your stack
- Slack
- Jira
- GitHub
- Docs

- Logs


Sagy Agent
Analyze. Load context. Execute workflows.

Context

Knowledge

Workflows

Tools
Workflow run
Flashed X2000 with 3.1.2
Started test server
Loaded console logs
Reproduced boot issue

Result
- Bug reproduced after 20 minutes
- Release 3.1.2 report loaded
- Possible cause: commit 08ee4d3
- Fix proposed
Continuously learns and improves with every runOne investigation layer, focused by domain.
Start with software incident investigation, then go deeper for firmware, hardware, and wireless systems where context is harder to recover.
Available now · Engineering teams
AI incident investigation for software teams
Gather context from Slack, Jira, GitHub, logs, docs, and databases, then preserve the validated investigation path.
Specialized agents
Available now
Wireless & Networking Devices
WiFi, Bluetooth, Zigbee, cellular. Routers, access points, repeaters, gateways, IoT radios.
More specialized agents coming soon
Engineering workflow automation grounded in context.
Step 1
Connect

Connect your tools so context flows automatically.
- Slack
- Jira
- GitHub
Step 2
Capture

Retain engineering knowledge from incidents and decisions.
- Discussions
- Incidents
- Decisions
Step 3
Create Workflows

Create custom workflows and skills for your specific use cases.
- Custom
- Reusable
- Versioned
Step 4
Execute Workflows

AI agents execute workflows with your context and connected tools.
- Accurate
- Consistent
- Actionable
Every execution makes your engineering team smarter.
Sagy's agents use workflows. These workflows learn from solutions found and issues closed, then update automatically so the next execution is better.

Every
- Incident resolved
- Merge request approved
- Design decision made
- Hardware issue debugged
- Production issue fixed
makes future workflows more effective.
The result is a company that gets smarter after every problem solved.
FAQ
Visit our help center to get in touch.
We're super responsive.