What problem this solves (and how)

Single source of truth in chat. Users ask questions; your app retrieves only what’s relevant from approved files and shows answers with structured references—no tab-hopping. Retrieval is powered by OpenAI’s File Search tool (vector stores + search results) or your own indexes.
Native UI, not a pasted wall of text. The Apps SDK renders components in an iframe via window.openai, so you can show result lists, citations, filters, and a “review & confirm” pane directly in the conversation.
Private context, governed. Connect secured repositories through MCP; require auth before exposing customer or deal content; enforce least-privilege scopes and human confirmations for any write actions.

Reference architectures (proven patterns)

A) Due-diligence “Data Room” for transactions

Flow: upload/ingest → search → compare → export packet
Pieces:

Retrieval: Responses API file search over a vector store (ingest PDFs, DOCX, CSV).
App surface: Apps SDK component lists hits (doc, section, score) with a preview panel; users can flag sections and export a summary.
Access control: OIDC/OAuth in the Apps SDK to gate private corpora; expose tools only after sign-in.

B) Internal policy & compliance Q&A

Flow: ask → retrieve policies → show sources → propose next steps

Use built-in file search to ground answers in your handbook/SOPs; show source references returned by the tool results in your UI. (File Search works via vector stores and returns results your app can cite.)
Keep the chat composer visible; use fullscreen only for long-form review per design guidance.

C) Board & investor briefings (read-only)

Flow: select meeting → question → curated packet

Read-only MCP tools fetch agenda decks and prior minutes from your DMS; your app renders a “briefing” view inline. (Mark any state-changing tools as write actions to trigger confirmations.)

How retrieval actually works (no magic, just contracts)

Ingest files → vector store. Upload files and build a vector store that File Search queries. This is the supported path for document retrieval with OpenAI.
Let the model call the tool. Via the Responses API, the model invokes file search when prompted; your app receives search results you can render (title, location/snippet).
Present citations cleanly. Use the search results to show precise “where this came from” references in your component. (Assistants-era docs describe file citations; with Responses you read the results payload and render your own.)

The ChatGPT app layer (UX that converts)

Inline first. Apps SDK components run in a sandboxed iframe and communicate via window.openai; keep tasks small (result list → details → export).
Discovery matters. The assistant chooses your app based on metadata—names, descriptions, parameter docs. Maintain a golden-prompt set and track precision/recall in Developer Mode.
When to use fullscreen. Only to deepen engagement (long document review), per design guidelines.

Security, privacy, and governance (review-ready)

Apps SDK is preview; submissions later this year. Plan for a review against App Developer Guidelines (privacy policy, accurate write-action labels, appropriate content).
Least privilege & confirmations. Validate inputs server-side; label any create/update/delete or egress as write actions so the client inserts human confirmation.
Plan & geo constraints. Apps run today for logged-in users outside the EU/CH/UK; EU is “soon.” Business/Enterprise/Edu can use Developer Mode but apps are not yet integrated in the client for those plans.

Build plan (4–6 weeks, scope-dependent)

Week 1 — Scope & contracts

Identify top Q&A intents (“compare vendor SLAs”, “summarize lease obligations”).
Define narrow MCP tools (e.g., search_docs(query), get_section(doc_id, loc)), and the App’s component structure.

Weeks 2–3 — Retrieval & UI

Ingest PDFs/DOCX/CSV into a vector store; wire file search in the Responses API.
Build the Apps SDK component (result list → preview → export). Test end-to-end in Developer Mode.

Week 4 — Auth & hardening

Add OAuth/OIDC if content is private; implement least-privilege scopes and confirmation UX for any writes.

Week 5 — Discovery optimization

Tune metadata; run your golden prompts and capture precision/recall results; verify mobile layouts.

Week 6 — Submission pack (when open)

Prepare screenshots, privacy policy, and support contact; confirm to the App Developer Guidelines.

KPIs you can instrument on day one

Answer groundedness: % of answers with ≥1 source shown (from file-search results).
Discovery precision/recall: from your golden-prompt set in Developer Mode.
Time-to-answer & abandonment after UI render (optimize component weight).
Coverage of corpus: % of high-value docs ingested into the vector store.

Common pitfalls (and how to avoid them)

Treating retrieval as a black box. Measure search quality and curate the corpus; File Search works best with clean, relevant vector stores.
Over-collecting data. The App Developer Guidelines require data minimization and a clear privacy policy; don’t collect sensitive data (PCI/PHI/IDs) in your submission.
Skipping discovery tests. Without metadata tuning + golden prompts, the model may not invoke your app consistently. Use Developer Mode and the testing guide.
Ignoring plan/geo limits. Plan EU rollout and Enterprise visibility separately until support lands.

RFP checklist (use with vendors)

Retrieval plan: vector-store design, ingestion scripts, quality metrics (recall/precision).
Apps SDK UX: component map (results, preview, export), window.openai event handling, mobile checks.
MCP contracts: tool schemas (read vs write) and authentication strategy.
Testing evidence: Developer Mode runs + golden-prompt report.
Compliance: alignment to App Developer Guidelines and Security & Privacy.

Why hire us

We build source-grounded Apps SDK experiences: contract-first MCP tools, vector-store retrieval, and in-chat UI that shows sources clearly—tested in Developer Mode and mapped to App Developer Guidelines + Security & Privacy so you’re ready when submissions open later this year.

Data Rooms & Q&A in ChatGPT: File Search, Retrieval, and Private Context with the Apps SDK