--- sidebar_label: Contract Intake sidebar_position: 6 description: External PDF intake for AI Access action-tool accounts; read-first users should use the in-app Upload Documents wizard. --- # Contract Intake Drop a contract PDF in chat — extract → review → transaction created in under a minute DocJacket can read a contract PDF, pull out the parties, addresses, key dates, and financials, and create the matching transaction. The standard workflow is the in-app **[Contract Extraction](/docs/ai-features/contract-extraction)** wizard. External AI contract intake uses the same extraction engine, but it requires AI Access action tools to be enabled for your account. If your connection is read-only, use the in-app wizard to upload, review, and save the transaction. ## What you can say When action tools are enabled, plain English works. The assistant picks the right tools based on what you ask: > "I just got this contract. Set up the deal." [paste or drop the PDF] > "Open this purchase agreement and start a transaction." > "Process this listing agreement." > "Extract this PDF and review with me before creating the deal." ## How it works The assistant walks the workflow for you. Behind the scenes: 1. **Upload.** Three paths, in priority order: - **(a) If the PDF is already in DocJacket** (DocDrop, email intake, the web wizard, or a prior chat call): the assistant calls `list_documents` to discover it, confirms with you ("found 'fl-buyer-purchase.pdf' uploaded at 9:14am — extract it?"), then `extract_existing_document(documentId)` starts the pipeline. PDF bytes never leave DocJacket. This is the canonical path and works in every assistant (Claude, Cowork, ChatGPT, Codex, Gemini) without any sandbox or paid-plan prerequisites. Just say *"extract the contract I uploaded this morning"* or *"process the file from earlier."* - **(b) If you attached the PDF directly in chat on Claude.ai with code execution enabled** (paid plan + `mcp.docjacket.com` added to allowed domains under Settings → Capabilities → Code execution): the assistant uses a two-step presigned upload — `request_upload_url` returns a short-lived URL, the assistant `curl`s the file from its sandbox to blob storage, then `kick_off_extraction` starts the pipeline. PDF bytes never enter the chat conversation. - **(c) Tiny PDF (~under 1 MB) attached in chat with no other option:** the assistant falls back to `upload_document_for_extraction`, which carries the bytes as base64 in the tool call. Avoid this path for anything larger — base64 inflates the file ~33% and lives in chat tokens for the rest of the conversation. Either way you get an `extractionJobId` and extraction kicks off in the background. 2. **Classify.** `classify_document` runs concurrently to detect the doc type — purchase agreement, listing agreement, lease, addendum, disclosure, etc. The classification informs which extraction prompt and checklist to use. 3. **Poll.** Extraction typically takes **10–60 seconds** depending on document length and complexity. The assistant polls `get_extraction_results` until the job is `completed` (or `failed`, in which case it shows the error and offers to retry). 4. **Review.** The assistant presents the extracted fields in chat: ``` 📄 Purchase Agreement — 1247 Pine Street Buyer: Sarah Smith (sarah@example.com) Seller: John & Mary Johnson Price: $625,000 · EMD $10,000 Closing: 2026-06-15 Inspection: 2026-05-25 (10 business days) Financing: 2026-06-01 (conventional, Wells Fargo) Listing: Mike Park, Park Realty Buyer agent: Casey Spaulding, Spaulding Real Estate Want me to create the transaction with these fields? ``` You can correct any field inline ("change the closing to June 18"), ask follow-ups ("is Mike Park already in my contacts?"), or just confirm. 5. **Apply.** On your "yes," and only when your AI Access connection has action-tool access, the assistant calls `apply_extraction`, which: - Creates the transaction with type detected (purchase / listing / lease) and side (buy / sell) - Adds every extracted party as a transaction contact with their role - Sets key dates on the transaction timeline (closing, inspection, financing, appraisal, EMD due) 6. **Done.** The assistant comes back with the transaction URL. You can keep going in chat with read tools such as `get_next_required_actions`, or pick up in the DocJacket web app. ## What gets extracted | Category | Fields | |---|---| | **Property** | Address (street / city / state / zip), MLS number, year built (when present), legal description | | **Parties** | Buyer(s) and seller(s) with names + email/phone when present; listing agent + brokerage; buyer agent + brokerage; lender contact; title company contact | | **Financial** | Purchase price, earnest money amount, loan type, loan amount, down payment, seller concessions | | **Key dates** | Contract date, closing date, inspection deadline, financing deadline, appraisal deadline, EMD due date, possession date, contingency-removal deadlines | | **Contingencies** | Inspection period (calendar or business days), appraisal contingency, financing contingency, sale-of-buyer's-home contingency | Standard state-association forms (TAR, CAR, FAR, MLS contracts) extract with highest accuracy. Custom forms work but may need more review. ## What gets created When you confirm `apply_extraction`: - ✅ **Transaction** in DocJacket with type + side detected - ✅ **All parties added** as transaction contacts (existing contacts are matched by email when possible to avoid duplicates) - ✅ **Key dates** populated on the timeline — inspection, financing, appraisal, closing, EMD due - ✅ **Key dates available for timeline/checklist workflows** after the transaction is created Everything is editable in the DocJacket web app afterward. ## Limitations to know about - **One PDF per call.** If the customer sent you a multi-document packet (contract + addenda + disclosures stapled into one PDF), use the in-app **[Smart Document Splitting](/docs/ai-features/smart-document-splitting)** wizard first to separate the docs, then run intake on the contract page-range. - **Purchase deals are most polished.** Listing-side and lease intake work but have less per-state customization. If a field looks wrong, just correct it in the review step. - **Per-state addenda are on the roadmap.** Today's extraction handles the main contract well; supplemental state forms (CA TDS, FL HOA disclosure, NJ attorney review rider, etc.) are best added through the web app after the transaction is created. - **Lead-Based Paint flagging is conservative.** The assistant will mention LBP applicability on every deal; if the property was built after 1978, just say "skip LBP" during review. - **Always review before confirming.** Extraction is very good but not perfect. A 15-second scan catches the occasional misread on a smudgy scan or non-standard form. ## Recovery — if you lost the chat Extractions don't depend on the chat window — they run server-side and stay queryable. If you closed Claude / Codex / ChatGPT mid-intake, open a new conversation and ask: > "Check my recent DocJacket extractions." The assistant calls `get_intake_status` and returns recent jobs with state — `processing`, `completed`, or `failed`. Completed jobs are still applicable; just confirm in the new chat and DocJacket finishes the intake. ## Try it now The fastest way to see it work: 1. Connect [Claude](/docs/ai-access/claude) or [Codex / ChatGPT](/docs/ai-access/codex) if you haven't. 2. Grab any sample purchase contract PDF. 3. Drop it in chat and say: *"Open this and set up the deal."* 4. Review the extracted fields, fix anything wrong, confirm. 5. Open DocJacket → Transactions — the new deal is there with parties, dates, checklist, and reminders. ## Read more - **[Connect Claude](/docs/ai-access/claude)** / **[Connect Codex / ChatGPT](/docs/ai-access/codex)** — install the connector if you haven't - **[Contract Extraction (in-app)](/docs/ai-features/contract-extraction)** — same engine, web-app workflow if you prefer not to use chat - **[Smart Document Splitting](/docs/ai-features/smart-document-splitting)** — split a multi-doc PDF first if you have one - **[AI Access overview](/docs/ai-access)** — section index