Workflow Advisory AI pipeline.

The problem

Inside Autodesk's Workflow Advisory platform, capturing consulting knowledge is a manual wall. Internal consultants enter workflows into an Airtable taxonomy field by field, then wait through a 3–4 month governance review before publication. Enterprise admins rebuild catalog workflows by hand in the Customize UI.

The second severe pain is that catalog fit assessment is entirely off-platform — the system surfaces workflows but cannot tell a user how relevant they are to their specific organization. This manual content creation is the primary bottleneck slowing platform adoption, and roughly 30% of workflows change about twice a year, so documentation constantly lags actual practice.

The solution

The AI Import feature turns unstructured source material into structured Workflow Advisory assets. A contributor uploads documents, images, or pasted text, and the AI extracts them into the platform's taxonomy, compares them against the published catalog, and recommends whether to adopt, customize, or add a new workflow.

The deliberate design choice is a single integrated pipeline — extract and compare run together in one pass — because ingestion without comparison leaves contributors unable to make disposition decisions. A Portfolio Summary surfaces every submitted workflow with fit scores and ranked catalog candidates, and no content enters the platform without explicit human approval.

How it works

The current build uses OpenAI gpt-4.1 via a Supabase Edge Function at temperature 0.4, chosen for structured JSON output, native vision for image-based sources, and a context window large enough to hold the full 471-workflow catalog. PDF text is extracted client-side; images are sent as base64 vision inputs.

An expert-analyst system prompt runs EXTRACT then COMPARE as one JSON response per workflow, with anti-fabrication rules requiring every field to be grounded in source material and per-field confidence scores flagging uncertainty. A V6 redesign is in progress, introducing function tools and a pgvector RAG store that retrieves top-K catalog candidates instead of injecting the whole corpus, keeping token cost flat as the catalog grows.

Who it's for

This is a strictly B2B enterprise feature. The buyer is a Digital Transformation Leader at a large enterprise account who signs the platform license and consulting contracts and is accountable for organization-wide digital outcomes.

The capstone primarily serves Bob, the internal Autodesk consultant who captures engagement IP into the published catalog and is the main contributor to catalog depth. A second persona, Sarah — a BIM Manager or Digital Lead configuring workflows for her organization — has her org-library path designed but deferred to a future phase. Engineers and contractors downstream consume the standardized processes.

Why it matters

Global digital transformation consulting was roughly $590B in 2024, growing about 20% CAGR. For Workflow Advisory specifically, the addressable market is 1,000–2,000 enterprise accounts representing $40M–$80M ARR, and each customer carries about $416K/year in internal manual workflow-management cost — putting the platform subscription at roughly 10x cost-displacement.

The differentiator is a flywheel generic AI tools cannot replicate: every consulting engagement contributes IP that makes the next one faster. The primary target is a 75% or greater reduction in time from raw engagement material to governance-ready submission, with the core message held constant — AI drafts, you approve — and the governance board's authority unchanged.

At a glance

Project

Workflow Advisory AI pipeline

Built by

Bridget Proulx

One-liner

This project helps Autodesk capture consulting knowledge and turn it into structured workflow assets inside Workflow Advisory.