Ask from the place your team already works
A staff member can ask Claude Cowork for a file note, strategy summary, advice pack, or QA check without assembling a perfect prompt from scratch.
Give Claude Cowork a governed path into AdviseWell, so your team can ask for file notes, strategy support, advice QA, Records of Advice, Statements of Advice, and presentation material without falling back to pasted notes and loose prompts.
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The Beta MCP connector gives Claude Cowork governed access to the full AdviseWell platform. Anything below can be requested by Claude in the agent loop, with adviser sign-off built in.
Claude Cowork is strongest when it can do more than chat. The AdviseWell pathway gives it a controlled way to request advice work, while keeping source material, templates, QA checks, and adviser review inside the workflow.
A staff member can ask Claude Cowork for a file note, strategy summary, advice pack, or QA check without assembling a perfect prompt from scratch.
The custom MCP pathway exposes scoped AdviseWell actions, so Claude Cowork requests advice work through a controlled interface rather than improvising the whole process.
AdviseWell returns source-aligned work such as Records of Advice, Statements of Advice, strategy documents, paraplanner requests, presentations, and QA notes.
Claude Cowork is valuable because it changes the behaviour from "ask a chatbot" to "delegate a piece of work." For advice firms, the opportunity is real, but only if delegation stays connected to sources, templates, QA checks, and adviser review.
The point is not another AI tab. The point is a work surface that can request approved actions, retrieve context, and return usable outputs without manual handoffs.
Claude Cowork can coordinate the request. AdviseWell supplies the advice-specific structure: document logic, source discipline, review standards, and house voice.
Clients can interrogate advice with their own AI. The advice pack needs to be coherent from meeting transcript to final recommendation, not just faster to produce.
For firms not already using Claude Cowork, the value is simple: your team can delegate more complete advice work in natural language, while AdviseWell keeps the work anchored to approved context and review gates.
Instead of asking AI for a generic draft, the team asks Claude Cowork to request a scoped AdviseWell action from approved advice context.
Advice outputs can come back with the underlying rationale, source alignment, and QA notes your team needs before anything is used with a client.
The demo is about how the workflow fits day to day: who can request what, what gets checked, and where adviser approval happens.
We will show the workflow in a live session and map what a custom MCP connector would expose to Claude Cowork for your firm.
We identify which AdviseWell actions Claude Cowork should be allowed to request: read context, draft documents, run QA, or prepare review materials.
AdviseWell can be exposed as a custom MCP connector so Claude Cowork has a governed way to request advice workflow actions.
We test a real-style advice task, confirm the review gates, and tune templates, prompts, and permissions before your team relies on it.
Sessions are run by senior members of the AdviseWell team, practitioners who understand advice production and custom workflow setup. We will show how Claude Cowork, MCP, and AdviseWell could fit together without handing you an ungoverned AI workflow.
AdviseWell is the AI advice OS for Australian firms. The Beta Claude Cowork MCP connector lets Claude Cowork request governed access to the full platform:
Claude Cowork runs in the agent loop. Anything above can be requested through the connector, with adviser sign-off built in.
No. The session can start with the business case: which advice tasks are worth delegating, where Claude Cowork could sit in the workflow, and which AdviseWell actions should be exposed first.
MCP gives Claude a structured way to connect with external tools and data sources. In this workflow, Claude Cowork is the interface and AdviseWell is the advice-aware system that handles source context, document generation, QA, and review outputs.
No. The point is controlled delegation, not autopilot advice. Claude Cowork can request work, AdviseWell can prepare and QA it, and your team still reviews the output before it is used with a client.
No. We can run the demo from our own realistic advice scenario. If you want to bring a live-style case, use an anonymised version with identifying details removed.
The exact tool set should be scoped with your firm. Useful starting points include file notes, paraplanner requests, advice strategy summaries, Records of Advice, Statements of Advice, PowerPoint presentations, and QA checks across the advice pack.
AdviseWell is built for advice firms that need stronger production, review, and compliance QA without adding more operational drag. It is especially useful when your team owns the quality of its advice documents, whether you are self-licensed, operating under an AFSL, or managing a growing advice function inside a larger group.
We send a short follow-up summarising what we covered, where AdviseWell could fit, and which parts of your advice flow or document set would be worth optimising first. No automated drip sequence. No sales pressure. If we think we're not the right fit, we'll tell you on the call.
Pick a time. We will show the custom MCP path, the advice workflow, and the review gates that keep agentic AI useful without losing control.
Book an Advice Workflow ReviewNo prep required. We can use a realistic advice scenario and map how this would fit your firm's governance and document workflow.