@Support Agent Prepare Northstar's launch plan before tomorrow's onboarding call. Include the open questions and confirm the account lead has seen it.
Maya Chen · Slack · #customer-success · 2m ago
People and AI coworkers share one workspace to hand off work, use your tools, and keep the team moving. Any model, any cloud, your infrastructure.
A request comes in. Agents use the tools and coworkers they need, then bring the result back to the team.
@Support Agent Prepare Northstar's launch plan before tomorrow's onboarding call. Include the open questions and confirm the account lead has seen it.
Maya Chen · Slack · #customer-success · 2m ago
Reading support threads0Read 18 support threads1.9s
Pulling account contextPulled account context1.2sNorthstar launch plan
The launch plan is ready, the open questions are included, and the account lead was notified in Slack.
Scheduled wakeup · 17:30
Double-check the launch plan and return only if the team is needed.

d5s for Sales teams
Review this morning's pipeline, flag deals that went quiet, and draft the follow-ups. Ask me before anything is sent.
Pipeline Agent
On it. I’ll review Attio, flag quiet deals in Slack, and prepare the Gmail drafts. I’ll come back before anything is sent.
SlackYou decide how they work. Set their permissions, tools, memory, and approvals in one place.
Every job gets its own workspace. Agents access only the files, tools, and network you allow.
You stay in the loop. See what your agents did, why they did it, and when they need you.
Northstar Organization
Shared policy · separate team workspaces
Product
4 people · 2 AI coworkers
Sales
3 people · 2 AI coworkers
Marketing
4 people · 2 AI coworkers
Finance
3 people · 2 AI coworkers
Operations
3 people · 2 AI coworkers
Keep people, agents, tools, and runs inside clear boundaries. Add organization-wide governance and your preferred deployment model as you scale.
Approve the providers and models your organization may use. Bring your own keys or run a self-hosted model.
Connect your identity provider. Give people and groups access to only the workspaces and agents they need.
Give every agent a role, approved tools, scoped data, and approval rules—then keep every action on the record.
Enterprise deployment
Deploy in single tenancy, inside your own VPC, or fully on-premise, in the region you choose. It can run completely air-gapped, with no third parties.
Bring the systems your team already uses and choose the organization-approved models behind each workflow.
Work across the systems your team already uses.




Use approved providers, your own keys, or models you host.
d5s is the AI agent workspace for teams that want frontier AI capability without the lock-in. Any model, any cloud, your infrastructure. Set up agents that handle repetitive work for the whole team, like clearing the support queue each morning, tracking suppliers, or pulling together the weekly report. Each one plugs into your existing tools, follows rules you write in plain language, and logs every step.
Teams that want AI doing real work, not just answering questions. Best fit: legal, finance, life sciences, infrastructure, and government suppliers, where data sensitivity rules out hosted chatbots. And teams that refuse to bet the business on one model provider: they match each task to the best model for the job, or the most cost-efficient one, and switch as the frontier moves, without re-platforming.
Request access. We onboard new teams with a short call, help define your first workflow, and connect it to one of your systems in the first session.
Hosted chatbots stop at the reply. With d5s, agents run in isolated sandboxes with scoped connectors to your real systems: reads logged, writes gated, every action under a policy your compliance team signed off on.
Depends on who hosts it. When we host it: in AWS, in the region you pick, isolated per customer, with infrastructure, identity, and model access handled for you. When you host it: inside your own cloud, in any region, behind your own login system. Data never leaves the environment you deploy into.
d5s does not use your data, prompts, or documents for model training. If your organization uses an external model provider, that provider's data handling depends on the model, account terms, and configuration your organization selects. Organization admins can restrict approved providers and models, bring their own keys, or use self-hosted models.
You pick. We handle access to OpenAI, Anthropic, Mistral, and others, or you bring your own keys, including open-weight and self-hosted models. Each agent is locked to a specific model, so switching providers is always explicit and reviewable.
One package covers the control plane, sandboxes, identity, and connectors. Deploy it inside your own cloud or on-premise, next to the systems your agents need to reach. Nothing has to leave your network.
Yes. Self-hosted setups plug into the identity provider your team already uses for single sign-on and access control, including fully air-gapped deployments where no traffic leaves your network.
Only the things you connect, with the permissions you set. Databases, SharePoint folders, Slack channels, internal tools. Each connection is read-only, write, or off, and you can change or revoke it any time.
Every run is sandboxed and destroyed when it finishes. Connector access is read-only, write, or off, and every read, write, and decision is logged for audit.
We're working with our first teams now. Tell us the job you'd want an agent to do, and we'll show you what it would look like.