Ops & Supply

How to vet and onboard vendors with AI

Ops & Supply3 AI tools7 steps6 friction points

Want an agent to handle this on your live data? See the Starch version →

Vetting and onboarding vendors is one of those workflows that looks straightforward until you're in the middle of it. You need to evaluate a supplier's financial health, legal standing, insurance coverage, and references — then, once you decide to move forward, collect W-9s, set up payment terms, get contracts signed, and document everything somewhere your team can actually find it. Most operators are running this process across email, PDFs, spreadsheets, and tribal knowledge, which means it's slow, inconsistent, and full of gaps.

The workflow feels like an AI problem because so much of it is information-dense but pattern-driven. Reviewing a vendor's certificate of insurance, summarizing a supplier's trade references, drafting an NDA, writing an onboarding checklist for a new logistics partner — these are tasks where the cognitive load is high but the actual judgment required follows a repeatable template. If you can describe the criteria, an LLM can apply them at scale and help you move faster without hiring a procurement specialist.

ChatGPT, Claude, and Gemini are genuinely useful here — for drafting vendor questionnaires, summarizing documents you paste in, generating contract language, and producing onboarding checklists from a template. They're good at taking unstructured information (a PDF you uploaded, a vendor's website copy) and organizing it against your criteria. What they can't do is connect to your actual systems, remember your vendor roster, or run automatically the next time you're evaluating a new supplier.

Skip the manual work → See the Starch version

Ops & Supply3 AI tools7 steps6 friction points

AI walkthrough

How to do it with AI today

A practical walkthrough using ChatGPT, Claude, and other off-the-shelf LLMs — what they're good at, what you'll have to do by hand.

Tools that work for this

ChatGPTClaudeGemini

Step-by-step

1 Start by building your vendor evaluation criteria in ChatGPT or Claude. Paste in your industry, typical vendor types, and any deal-breaker requirements (e.g., minimum insurance limits, required certifications, payment terms), and ask it to generate a structured vetting scorecard with weighted categories.

2 Use Claude or ChatGPT with file upload to review vendor documents. Upload a certificate of insurance, a supplier's capability deck, or a W-9, and prompt the model to extract key fields and flag anything that doesn't meet your stated criteria.

3 Draft your vendor questionnaire in ChatGPT or Claude. Describe your business, the vendor category, and what you need to know, then ask it to write a 10-15 question due-diligence form you can send as a Google Form or email attachment.

4 When a vendor responds to your questionnaire, paste their answers back into the same conversation and ask the model to score them against the scorecard you built in step one. Ask it to surface the top three concerns and a go/no-go recommendation.

5 For contracts, paste your standard vendor agreement (or ask the model to draft one from scratch) and use Claude or ChatGPT to redline specific clauses — indemnification, IP ownership, termination rights — based on your stated requirements.

6 Build a vendor onboarding checklist by describing the vendor type and your internal setup process. Ask the model to produce a sequenced task list covering document collection, system access, payment setup, introductory calls, and milestone check-ins.

7 Paste your completed checklist into your project management tool or a Google Doc manually. The model has no connection to your task tracker, so you're copy-pasting outputs into wherever your team actually works.

Prompts you can copy

You are helping me vet a new logistics vendor. My requirements: $1M general liability insurance minimum, references from at least two companies in CPG, payment terms of net-30 or better. Here is their questionnaire response: [paste]. Score them on a 1-10 scale per category and flag any disqualifiers.

Draft a vendor due diligence questionnaire for a software development subcontractor. Include sections on company background, financial stability, data security practices, IP ownership, and client references. Keep it under 15 questions.

Review this certificate of insurance [paste text] and tell me whether it meets the following minimums: $1M general liability, $500K professional liability, $100K cyber liability. Flag anything missing or expiring within 90 days.

Draft a standard vendor NDA for a US-based manufacturing partner. Include mutual confidentiality obligations, a 2-year term, carve-outs for publicly available information, and governing law of Delaware.

Create a vendor onboarding task list for a new marketing agency. Include: signed contract, W-9 collection, bank details for ACH setup, tool access provisioning, a kick-off call agenda, and a 30-day check-in milestone.

Reality check

Where this gets hard

The walkthrough above works — until your numbers change, the LLM hallucinates, or you have to re-paste everything next month.

No connection to your existing vendor records — every session starts with a fresh paste, so the model has no memory of which vendors you've already vetted or what terms you negotiated last time.

Document review is one-at-a-time and manual — you upload one PDF, prompt the model, copy the output. There's no way to run 12 vendor certificates through the same evaluation criteria automatically.

Contract drafts and scorecards live in the chat window. Nothing gets saved to a shared repository; next week a teammate runs the same prompts from scratch and gets slightly different output.

The model can't route anything — it produces an onboarding checklist but can't assign tasks to your team, trigger a contract signature request, or send a follow-up email to the vendor with the W-9 link.

Outputs aren't consistent between runs. The scorecard structure you carefully tuned last quarter won't be reproduced exactly unless you save and re-paste the full prompt every time.

No connection to QuickBooks, your CRM, or your file storage — so verifying whether a vendor already exists in your system, checking outstanding invoices, or pulling prior contract terms requires manual cross-referencing outside the chat.

Tired of the friction?

Starch runs the whole workflow on live data — no copy-paste, no hallucinated numbers, no re-prompting next month.

See the Starch version →

Starch alternative

The same workflow on Starch

Starch is an agentic operating system — it builds the persistent app your vendor vetting and onboarding process actually runs on, connected to your live data, instead of a one-off prompt chain you re-run manually each time.

Connect QuickBooks from Starch's integration catalog — the agent queries vendor records, outstanding bills, and payment history live when your vetting app needs them, so you're not manually cross-referencing your accounting system.

Connect Gmail or Outlook and Starch can automate vendor document collection: send the intake questionnaire, track responses, and surface incomplete submissions without you monitoring an inbox manually.

Describe your vendor scorecard in plain English — 'build me a vendor vetting tracker that scores suppliers on insurance coverage, references, payment terms, and security posture, and flags anything below threshold' — and an agent builds it as a persistent app your whole team uses.

Contract Lifecycle Management is coming soon — it will handle contract drafting from a clause library, multi-party e-signature routing, and a searchable repository with full audit trail, all from the same operator stack.

Use Starch's Project Management app to turn onboarding checklists into assigned tasks the moment a vendor is approved — tell Starch 'create an onboarding project for [Vendor Name] with these steps, assign intake tasks to ops, and set a 30-day check-in reminder' and it builds the task structure for you.

Browser automation means Starch can reach vendor portals, government business registries, or insurance verification sites that have no API — it navigates them the way a human would, no integration required.

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