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What GTM Workbench is

GTM Workbench is an AI-assisted workspace where agents and workflows turn your source material — sales-call transcripts, documents, URLs — into publishable artifacts: case studies, one-pagers, emails, LinkedIn posts, and briefs. It is deliberately human-in-the-loop (HITL). The agents handle analysis and first drafts; you curate, approve, and refine at every stage. This is intentionally not a black-box, fully automated pipeline — you stay in control of what ships.
Workbench is a flagship example of what teams build on the Corbits agentic platform. We run it internally to move our own go-to-market work — so the platform primitives it depends on (identity, agent lifecycle, credentials and grants, native workflows, and skills-as-assets) are proven in production, not just documented.
It’s built for sales and marketing teams who want to turn call insights into usable content quickly, without waiting on a content team.

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Meet Myra, your chief of staff

Every user gets a personal AI agent named Myra, framed as a chief of staff and executive assistant. Workbench opens into your Inbox, not a chat window. The Inbox is your mailbox in Workbench. Chat with Myra is its own surface, reachable from the Threads entry in Workbench’s sidebar.

Parallel threads

Run multiple Myra threads at once. Each thread is a full agent with its own tools and history — not just a saved transcript — so you can keep separate lines of work going in parallel.

Shared memory

Myra’s durable memory is shared across all of your threads. What she learns in one chat — standing facts, context, contacts — is available in the others.

Works with your files

Attach an image or a PDF to a message. Myra reads images directly and understands PDFs through a dedicated file parser, so documents work regardless of her underlying chat model.

Reuses your artifacts

Myra can read a document you or a workflow saved earlier as an artifact, so prior work becomes input for the next task.

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The agent roster

Myra is the agent you talk to, but she isn’t working alone. A roster of specialists handles focused parts of the job (processing calls, research, writing, humanizing), and Myra brings them in as a job needs them.

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The source-to-artifact model

Workbench follows one product rule: you choose outcomes, not pipeline topology. You bring source material, pick the outcome you want, review the decisions that matter, and approve usable artifacts. The internal steps stay hidden. That model is built from a small, consistent vocabulary: The visible flow is short and predictable:
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Choose your source

Select the material a Job should work from — call documents, uploaded files, URLs, or an artifact from earlier work.
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Choose an outcome

Pick an Offering that describes what you want to produce. You select the outcome; the workflow decides how to get there.
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Review findings

At a review gate, the Job shows you what it found and asks for the decision that matters — which findings should drive the content.
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Approve artifacts

Approve, reject, or request refinement on each generated artifact before it counts as done.
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Export

Copy, download, or hand off approved artifacts through an optional delivery Hook.
Every Job streams its progress in a single, generic run console. There is no bespoke per-workflow screen to learn — the same review surface handles confirming sources, selecting findings, and approving artifacts across every outcome. When a Job reaches a review gate, it pauses and waits for your approval before continuing.

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Integrations and tools

Agents don’t only write. They reach into the systems your team’s work already lives in, and Myra decides which tool a task needs, pulling in more on demand. These are the providers wired today; each is a tool package, so the set grows without reworking the app.

CRM (Attio)

Read records, tasks, and workspace members from Attio, and add notes or update tasks, so call insights and approved copy land on the right account.

Project tracking (Linear)

Read issues, teams, users, and projects from Linear as context for the collateral you’re producing, and write back to it. This is a full read/write integration: alongside creating issues, commenting, and updating documents, projects, and milestones, it can archive and delete issues and manage webhooks. Each of those writes is authorized against a grant and held for your approval before it runs, unless you have auto-approved that specific tool.

Publish to the web (Vercel)

Deploy an approved HTML artifact to a public Vercel URL. Publishing is irreversible, so a deploy is held for your approval in a review gate before it runs, and defaults to a preview URL.

Web and social research

Search the web (Exa), crawl and extract structured content from any site (Firecrawl), and run read-only searches across Hacker News, GitHub, Bluesky, and creator platforms.
Myra doesn’t carry a fixed toolbox. Skills aren’t attached up front: she searches the library and loads only the ones a thread turns out to need. Long-tail tools work the same way (the CRM and the rest stay out of her way until she pulls them in), so new skills and integrations reach her without a change to the app.
Every tool call is authorized against a grant, and write tools require your approval by default. Irreversible steps like a web deploy are held for your approval before they execute. See Credentials and guardrails.

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Skill Library

Upload, browse, and version reusable AI instruction sets — the prompts, personas, and procedures that shape how agents respond. Inspect a skill’s files, review its version history, and restore any prior version. Attach a skill to an agent to change its behavior.

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Insights and analytics

A Data & Insights surface shows how the workspace is actually being used: who is running what, which workflows produce the most, and what it costs.

Usage by person

Token and turn usage attributed to each member, so you can see who is getting value from the workspace.

Workflow runs by kind

Activity and token usage grouped by workflow type, so the outcomes people run most are easy to spot.

Token and cost tracking

Input, cache, and output tokens are kept separate and priced from open models.dev rates, for an honest read on spend.

Run traces

Open any run’s full trace, or scan a workspace-wide activity timeline where every entity links into its own history.

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Built on the Corbits platform

Workbench doesn’t reinvent the hard parts. It relies on the Corbits agentic platform for the primitives every serious agentic product needs, enabling agents and agentic workflows to seamlessly integrate into the team’s day-to-day operations.
The platform provisions each user’s personal Myra instance and manages the lifecycle of every agent and workspace worker. Workbench doesn’t build its own identity or agent-runtime layer.
Inference and tool credentials are stored and resolved by the platform, and every tool call is authorized against a grant. Members never enter API keys, and access is scoped by the platform rather than a hand-rolled permission model.
Workflows are deployed definitions that run on the platform’s native workflow runtime — durable runs, review-gate signals, and event logs included. Adding a new workflow is a new package and a push, not a rewrite of the app.
The Skill Library is backed by the platform’s asset substrate, which owns storage and versioning. Workbench never reimplements how skills are stored or versioned.

Platform overview

See the agentic platform Workbench is built on.

Credentials and guardrails

How credentials, grants, and delivery capabilities are governed.

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Why teams use it

Fast

Select your sources, pick an outcome, and get draft collateral in minutes.

Reviewable

Every stage is human-approved. No black-box automation deciding what ships.

Resumable

Jobs and sessions are saved, so you can step away and come back to iterate.

Exportable

Approved artifacts are ready to copy, download, or deliver through a Hook.