LandingAI Agentic Document Extraction (ADE) and Google Pinpoint both help people work with difficult documents, but they are built for different jobs. ADE is an API-first document-processing platform for turning documents into structured, source-grounded data used by software systems. Pinpoint is an AI-powered research workspace for journalists, academics, and content creators who need to search, analyze, and collaborate over document collections.
Choose ADE when a production application needs repeatable parsing, schema-controlled JSON, asynchronous processing, or field-level evidence that can be passed to a review interface. Choose Pinpoint when researchers need an interactive workspace for searching collections, asking questions with Gemini, transcribing media, highlighting evidence, and collaborating with other people. For many teams, this is not a replacement decision: Pinpoint supports human-led research, while ADE supplies document data to applications and automated workflows.
What LandingAI ADE and Google Pinpoint Are
LandingAI ADE is a developer-facing document-processing platform. Its current workflow separates three tasks:
- Parse converts a document into reading-order Markdown and a hierarchical structure of elements such as text, tables, figures, and table cells.
- Extract uses a JSON schema to return selected fields as structured data.
- Ground maps extracted evidence back to parsed blocks, pages, and bounding boxes so an application can show where a value came from.
The current ADE v2 production APIs are Parse and Extract, with synchronous and asynchronous job options. Developers can call them through REST, Python, or TypeScript and connect the results to databases, review tools, RAG systems, agents, or business applications.
Google Pinpoint is an AI-powered research platform. Users create collections, upload source material, search across thousands of files, organize evidence, transcribe audio, collaborate, and ask Gemini questions about the collection. Gemini responses include supporting evidence from the uploaded documents. Pinpoint also identifies entities and provides tools for extracting similar tables into downloadable data.
The practical distinction is the operating model. ADE is designed to be called by software and return machine-usable output. Pinpoint is designed primarily for people conducting research in a Google-hosted interface.
Document Types
Both products accept varied source material, but their format support serves different outcomes.
ADE v2 supports PDFs, common image formats, DOCX, ODT, RTF, PPTX, XLSX, and CSV. It is suited to visually complex business documents such as contracts, invoices, statements, reports, forms, technical manuals, medical records, and mixed-layout scans. Parse preserves document hierarchy and reading order; Extract returns fields defined by the developer's schema. Teams should verify the latest format, page, and file-size limits in the ADE supported-file documentation.
Pinpoint accepts PDFs, images, audio, video for audio transcription, email, web pages, Google Docs and Slides, Microsoft Word, Excel and PowerPoint files, plain text, and Markdown. Most non-audio inputs are converted to PDF, and Google applies OCR to non-audio files. Its supported-file documentation states that OCR can analyze printed and handwritten text in PDFs, including text inside embedded images.
| Capability | LandingAI ADE | Google Pinpoint |
| Primary document goal | Produce structured data for software workflows | Help people research a collection |
| PDFs and scans | Yes | Yes |
| Images | Yes | Yes |
| Office documents and spreadsheets | DOCX, ODT, RTF, PPTX, XLSX, and CSV in ADE v2 | Word, Excel, and PowerPoint; most inputs converted to PDF |
| Audio and video | Not a core ADE v2 input workflow | Audio transcription; video audio is extracted and transcribed |
| Schema-defined JSON | Yes, through Extract | Not documented as a general-purpose API output |
| Collection search and collaboration | Built by the customer around ADE output | Native Pinpoint workflow |
| Table workflow | Parses table structure and can extract schema-defined fields | Can convert selected, similarly structured tables into downloadable CSV or XML |
Pinpoint's structured-data tool is useful when a researcher has many documents with similar tables, but it is not equivalent to a general extraction API. Google's instructions require the user to annotate the table to extract. See Extract structured data from your collection for the current workflow.
Provenance and Auditability
Both products can help a user check output against source material, but the evidence is exposed differently.
ADE is designed for programmatic, field-level traceability. Parse returns source metadata for document blocks, including the page, a Markdown character range, and normalized bounding-box coordinates. Extract returns the source ranges that support schema-defined values. Ground connects those ranges to the corresponding Parse blocks so a review application can display the original page region beside the extracted field. The ADE Ground documentation explains this source-mapping step.
Pinpoint provides evidence within its research experience. Gemini answers can include supporting passages from collection documents, and users can open the source material to inspect the relevant text. Search, highlights, labels, and collection sharing support a human research trail. Collections are private by default, and owners control collaborators and publication. Google's collection-management documentation explains those access and sharing controls.
| Requirement | LandingAI ADE | Google Pinpoint |
| Show supporting source | Yes | Yes, within research and Gemini workflows |
| Page-level source reference | Returned in parsed structure | Source document can be opened from the interface |
| Bounding-box coordinates | Returned for grounded Parse blocks | Not documented as a general machine-readable output |
| Field-level machine verification | Extract ranges can be grounded to page regions | Evidence is optimized for human review in Pinpoint |
| Review outcome tracking | Customer builds or integrates the review workflow | Highlights, labels, collaboration, and collection activity support research review |
| Downstream audit system | Structured output can be stored with application records | No general-purpose extraction API is documented for this use |
Choose based on the audit artifact you need. If a reviewer must inspect citations while researching, Pinpoint's native evidence experience may be sufficient. If an application must retain field values with page and coordinate evidence, ADE offers the more direct programmatic model.
Deployment and Access
ADE is available as a hosted service in US and EU environments. LandingAI also documents Enterprise deployment options for a containerized application in a customer's VPC on AWS, Azure, or Google Cloud, as well as on-premises deployment. Zero Data Retention is an optional control on eligible plans. With ZDR enabled, LandingAI states that customer data is not persisted beyond processing and is not used to train or improve its models. Security, residency, contractual terms, and deployment responsibilities should be confirmed for the selected configuration through LandingAI's security documentation.
Pinpoint is a Google-hosted web service accessed with a Google Account. Collections are private by default, but users can share them or publish eligible collections. Google states that documents uploaded privately are not used to train large language models. Pinpoint copies imported file contents into the service, and Google describes Pinpoint as an Additional Google service, meaning Google Workspace terms do not apply to its use. Organizations should review the Pinpoint privacy and data-access disclosures and verify whether their Workspace administrator permits access.
Google's public Pinpoint documentation does not describe a customer-VPC or on-premises deployment. Organizations that require processing inside their own controlled environment should not assume that a private collection satisfies that requirement.
Pricing
LandingAI ADE uses credit-based pricing. The Explore plan includes free credits for evaluation, the Team plan adds higher limits and eligible controls, and Enterprise pricing is customized for deployment, scale, support, and commercial requirements. Parse and Extract consume credits according to the operation and the amount of document or output content processed. Check the current Agentic APIs pricing page before estimating production cost.
Google states that it does not charge a fee for Pinpoint read-only or full access. A valid Google Account is required, and full collection access is oriented toward journalists, academics, and content creators. Pinpoint for Professionals provides higher storage, upload, processing-priority, transcription, and Gemini limits to approved users. Review the current Pinpoint access requirements and Pinpoint for Professionals limits before planning a large research project.
Pricing should be compared with operating cost, not only license cost. For ADE, include API consumption, application development, review, and storage. For Pinpoint, include researcher time, access eligibility, quotas, manual export, and any work required to move findings into operational systems.
Decision Table
| Requirement | Better fit | Why |
| Interactive research across a large collection | Google Pinpoint | Native search, entities, labels, Gemini Q&A, evidence review, transcription, and collaboration |
| Production document extraction API | LandingAI ADE | REST and client libraries return reusable structured output |
| Schema-controlled JSON fields | LandingAI ADE | Extract accepts a JSON schema and returns selected values with source ranges |
| Journalistic or academic investigation | Google Pinpoint | Designed for researchers working directly with collections |
| Audio transcription alongside documents | Google Pinpoint | Audio and video-audio transcription are documented features |
| RAG or agent ingestion | LandingAI ADE | Reading-order Markdown and typed, grounded structure are designed for downstream systems |
| Machine-readable field provenance | LandingAI ADE | Ground connects extracted ranges to page and bounding-box evidence |
| No-fee human research workspace | Google Pinpoint | Google documents no fee for read-only or full access, subject to access requirements and quotas |
| Private VPC or on-premises requirement | LandingAI ADE | Enterprise deployment options are documented; confirm scope and terms with LandingAI |
| Search findings and collaborate without building an application | Google Pinpoint | The research interface and collection controls are already provided |
The short answer is simple: choose Google Pinpoint for human-led research, and choose LandingAI ADE for production software that must turn documents into structured, traceable data. If a workflow needs both, researchers can use Pinpoint to investigate a corpus while developers use ADE to feed verified document data into operational applications.
Frequently Asked Questions
Is Google Pinpoint a document extraction API?
Google describes Pinpoint as an AI-powered research platform, not as a general-purpose document extraction API. It can OCR documents, transcribe audio, identify entities, answer questions with supporting evidence, and extract annotated tables. Teams needing automated, schema-defined output for an application should evaluate a production extraction API such as ADE.
Can Google Pinpoint extract structured data from documents?
Yes, within a specific workflow. Pinpoint can extract data from similarly structured tables and export it as CSV or XML, but users must annotate the table they want to extract. This differs from ADE Extract, which accepts a JSON schema for requested fields and returns machine-readable values with supporting source ranges.
Which is better for source citations and audit review?
It depends on the review model. Pinpoint gives researchers supporting evidence inside its interface so they can inspect Gemini answers and source documents. ADE returns machine-readable page, range, and bounding-box grounding that developers can store or display beside individual extracted fields. Test whether the evidence remains complete and correct on your own documents.
Can either product run inside a customer-controlled environment?
LandingAI documents Enterprise options for deployment in a customer VPC or on premises. Google Pinpoint is documented as a Google-hosted service accessed through a Google Account; its public documentation does not describe customer-VPC or on-premises deployment. Confirm technical and contractual details with each vendor before processing restricted data.
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