Enterprise memory for everyteam
Capture team context, keep it governed, and surface it for the people and agents doing the work.
One memory layer for work, tools, and agents.
Capture approved work context. Keep it governed. Make it useful for people and agents.
Capture work automatically
Capture approved context from apps, browsers, meetings, files, and desktop activity.
- Apps and terminals
- Browser activity
- Meetings and audio
Search business memory
Ask questions across remembered work with sources, time, and permissions in view.
- Time-aware retrieval
- Source-grounded answers
- Cross-tool search
Ready for agents
Give agents the context they need, with admin control over sources and access.
- Agent-ready context
- Model and source routing
- Human-in-the-loop controls
Admin controls
Manage source access, sharing, retention, exports, and model routing from day one.
- Source-level access
- Audit and retention controls
- Enterprise deployment support
Capture. Preserve. Resurface.
Pieces turns approved work activity into governed memory, then brings the right context back when teams need it.
Capture
Capture approved app, browser, meeting, and desktop context locally.
Preserve
Create timeline summaries and source-linked context automatically.
Resurface
Pieces Desktop, MCP-ready tools, and your agents tap the same captured context.
One memory layer for every department.
Reuse engineering context faster.
Find fixes, commands, PR context, and incident history before work repeats.

Governed by your controls.
Keep memory local by default. Route approved requests through your VPC, keys, and audit logs.
Control access, models, and retention.
- SSO, roles, source access, and audit trails.
- Local LLMs or BYOK cloud providers in your account.
- SOC 2 Type II with retention, residency, and export controls.
- Policies scoped by team, source, workflow, or data class.
Start small. Scale where your enterprise runs.
Deploy on devices, managed fleets, private cloud, VPC, on-prem, or offline.
Local-first, cloud-augmented
Keep memory on device. Route approved prompts to hosted models only when policy allows.
Your cloud, your keys
Use AWS Bedrock, Google Vertex AI, or Azure OpenAI in your account.
Flexible or custom deployment
Support air-gapped, regional, offline, and custom-auth environments.
- On-prem
- Offline
- Hybrid
Make work context useful while it is fresh.
Pieces helps teams reuse decisions, fixes, calls, and handoffs before knowledge disappears.
Reduce repeated work
Find prior fixes, decisions, calls, and handoffs before repeating work.
Shorten ramp time
Help new employees learn from real workflows, not stale docs.
Context-aware answers
Give models source-grounded business context, not broad uploads.
Questions before a pilot.
Clear answers for security, IT, and teams evaluating enterprise memory.
What does Pieces capture?
Pieces captures approved work context from applications, browsers, meetings, files, clipboard, and desktop activity. Capture is scoped by policy and can be adjusted by team or workflow.
Where does enterprise memory live?
Memory is local-first and can stay on device. If your organization enables cloud sync or model routing, it follows your deployment, security, and retention policy.
How do admins control access?
Admins can set source access, roles, retention, model routing, export controls, and audit requirements. Private work can remain private unless sharing is explicitly enabled.
Which AI models can teams use?
Teams can use approved providers such as OpenAI, Anthropic, Gemini, AWS Bedrock, Google Vertex AI, Azure OpenAI, or local models. Routing can vary by team, source, or data class.
Can Pieces fit our deployment model?
Yes. Pieces can support local-first, cloud-augmented, VPC, private cloud, regional, on-prem, offline, and custom-auth deployment paths.
What does a pilot look like?
Start with one team and a defined set of approved sources. We align model routing, security requirements, success criteria, and rollout steps before expanding.
Ready to bring Pieces to your team?
Run a focused pilot with your security requirements, preferred models, and deployment boundaries.



