◎AI Agent Workspace

AI Agent Workspace for Teams.

Buda is a cloud-native AI agent workspace where teams run persistent agents with shared memory, files, Browser, Terminal, Git, and human review in one place.

✓One workspace for every agent
✓Persistent memory from real work
✓Team review stays visible
The gap

Agents keep starting from scratch.

01
Context lives outside the run.

Agents lose the previous files, decisions, account notes, code changes, and review comments that make the next run useful.

02
Tools fragment across tabs.

Real work needs browser research, terminal output, Git diffs, Drive files, CRM records, and docs.

03
Handoffs stay private.

One person runs the agent, another teammate reviews a summary, and a manager asks for proof.

04
Outputs need review.

Teams need briefs, drafts, tables, PR notes, CRM updates, and reports they can inspect before anyone acts.

Agents keep starting from scratch.
Why Buda

Build a workflow around AI Agent Workspace.

One workspace for every agent

One workspace for every agent

Each workflow gets a shared Drive, connected tools, agent roles, and a review queue. Researchers, builders, reviewers, and operators work from the same source context.

See the building blocks →
Persistent memory from real work

Persistent memory from real work

Buda preserves the files, outputs, decisions, and prior runs that matter. Agents can continue a workflow instead of asking the team to re-upload the same context.

Start with context →
Team review stays visible

Team review stays visible

Every meaningful output becomes an artifact the team can inspect. Owners, sources, status, and execution history stay close to the work.

See workflows →
Capabilities

The practical building blocks behind AI Agent Workspace.

Specialized agents. One shared workspace. Every output is a reviewable artifact, not a black box.

🧠 SDR / AE

Persistent agent memory

Agents build on prior research, files, messages, decisions, and outputs across sessions.

Persistent agent memory
📁 Tech Lead

Shared Drive context

Source files, drafts, outputs, and working documents stay close to the agents using them.

Shared Drive context
☁️ Ops Lead

Cloud-native execution

Run agent work from the browser without managing local machines, self-hosted servers, or dedicated hardware.

Cloud-native execution
⌘ Founder

Browser and terminal work

Give agents a workspace for web research, page inspection, file operations, commands, and technical tasks.

Browser and terminal work
⑂ SDR / AE

Git-aware engineering work

Keep diffs, issue context, test output, PR notes, and release artifacts in the same workspace.

Git-aware engineering work
✓ Tech Lead

Reviewable artifacts

Buda turns agent activity into briefs, drafts, tables, reports, CRM updates, PR notes, and action lists.

Reviewable artifacts

Spin up your ai agent workspace pod in 30 minutes.

Pick a workflow, assign the agents, and review the first artifact. Free pilot, no credit card.

Use cases

Start with the workflow that hurts today.

Pick one workflow with repeated demand, visible ownership, and measurable output.

01SDR / AE

Sales account research

Collect company context, buying signals, stakeholders, and past notes, then draft a reviewed account brief and first-touch message.

Start this workflow →
Sales account research
02Tech Lead

Engineering review prep

Inspect diffs, summarize risk, suggest tests, and prepare release notes from Git context and issue history.

Start this workflow →
Engineering review prep
03Ops Lead

Operations reporting

Gather dashboard exports, internal notes, and workflow exceptions into a weekly report with owners and next steps.

Start this workflow →
Operations reporting
04Founder

Founder research loops

Turn market pages, customer notes, competitor research, and product decisions into a living research workspace.

Start this workflow →
Founder research loops
Pilot plan

Start with one useful workflow, then expand.

Four weeks. One workflow. A clear, measurable outcome before you scale.

01Week 1

Choose one workflow

Start with Sales account research. Keep the output easy to review.

02Week 2

Assign agents and controls

Create the workspace, invite members, and define files, tools, and usage boundaries.

03Week 3

Measure output and spend

Review artifacts, usage, ownership, and execution history before expanding scope.

04Week 4

Expand or stop cleanly

Repeat proven work in another team, or retain the governed record and stop.

AI Agent Workspace

Give your team one workspace for AI agents.

Start with one workflow, give it persistent context, assign the right agents, and review the first artifact in Buda.

✓ Free pilot · No credit card · Live in 30 minutes