Gemini 3.1 Pro for Multimodal Document Pipelines

A document pipeline becomes difficult when the answer depends on both words and layout. A scanned invoice may place its total beneath a stamp. A technical report may explain a chart several pages after it appears. A useful workflow must preserve those relationships, extract consistent records, and make uncertain results easy to review.

This walkthrough shows how to organize that workflow around Gemini 3.1 Pro, with Quanta handling API access and usage accounting. The central design choice is to treat every extracted value as a claim that needs a source.

01 · Step 1: Define the record before submitting documents

Start with one document family, such as invoices or inspection reports. Write down the fields your downstream system needs, their expected types, and the evidence required for each. For an invoice, that might include the supplier, invoice date, currency, subtotal, tax, and total.

Specify how missing information should appear. Use null for an unreadable amount instead of inviting a guess. Keep extraction separate from business decisions: the model can identify payment terms, while your application decides whether those terms meet policy.

02 · Step 2: Preserve page identity and visual context

Assign each document a stable identifier and retain its original file. Check the input formats and request limits supported by the Gemini 3.1 Pro route you intend to use. Confirm how that route accepts documents or page images before building the ingestion layer.

When rendering pages, preserve page numbers and enough resolution to read small labels. Include the complete page when layout matters. A tightly cropped amount can lose the heading that distinguishes a subtotal from a balance due. For long documents, split at meaningful boundaries and retain a manifest connecting every segment to the original.

03 · Step 3: Connect Quanta and verify the request format

Quanta provides a pay-as-you-go API relay with one balance across its supported models. Open a Quanta account, create an API key, and configure your OpenAI SDK integration to use https://api.quantarelay.com as its API base address, following the documented endpoint requirements.

Check the exact model identifier and multimodal request format for Gemini 3.1 Pro. SDK compatibility does not guarantee that every provider accepts identical file attachments or content fields. Submit one representative document first, then confirm that the response actually reflects its visual content before increasing volume.

04 · Step 4: Request structured fields with page evidence

Give the model a narrow task: extract the specified fields, preserve printed units and currencies, and attach a page reference and supporting text to each result. Ask it to distinguish directly observed values from values calculated from other fields.

Treat document contents as source material. Explicitly instruct the model to ignore instructions embedded in documents, including requests to change the output format or reveal credentials. Keep API keys and unrelated internal data outside the extraction context.

• › Value: The extracted content, or null when unsupported.
• › Evidence: The page number and a short supporting quotation or visual description.
• › Status: Observed, calculated, missing, or ambiguous.

05 · Step 5: Validate results before accepting them

Parse responses against your schema and reject malformed records. Apply deterministic checks for dates, allowed currencies, required fields, and arithmetic relationships. If line items do not reconcile with the total, flag the discrepancy rather than silently replacing the printed figure.

Send ambiguous fields to review with the relevant page attached. A model’s confidence statement is not proof of correctness. Reviewers should be able to compare the extracted value with its source without searching the entire document.

06 · Step 6: Measure tokens, caching, and retry costs

Run a representative evaluation set containing clean pages, poor scans, dense tables, and missing fields. Measure field accuracy and review effort alongside token consumption. Quanta meters calls on real tokens and prices cache writes and cache reads separately, so track those categories independently.

Keep reusable instructions stable where supported caching behavior makes that useful. Verify cache eligibility and reported usage instead of assuming repeated content is free. Retry failed segments selectively, with bounded attempts, to avoid paying repeatedly for an entire document.

07 · Step 7: Expand only after the evidence holds up

Version your prompts, schemas, and model settings. Recheck the evaluation set whenever one changes. If you test Gemini 2.5 Flash for simpler documents, compare it against the same acceptance criteria. Quanta’s shared balance makes such comparisons convenient; your evidence and validation rules determine which route belongs in production.