Data extraction companies, products & suppliers

Data extraction products pull defined fields from documents, emails or web sources into structured records. Unlike general Document AI, the buyer usually brings a schema. The assurance question is field-level accuracy and how source files are stored.

What is Data extraction?

Data extraction products pull defined fields from documents, emails or web sources into structured records. Unlike general Document AI, the buyer usually brings a schema. The assurance question is field-level accuracy and how source files are stored.

What problems does it solve?

Defined fields still live in PDFs and inboxes.

Typical business use cases

  • Claims intake
  • Onboarding packs
  • Web-to-record

Important capabilities

  • Schema mapping
  • Validation
  • Human correction
  • APIs

What buyers should evaluate

  • Field accuracy
  • Schema flexibility
  • Training data

Risks and governance considerations

Silent field errors in downstream finance or KYC.

Procurement checklist

  • Field SLAs
  • Review queue
  • Source retention

Relevant AI Trustmark assurance

Extraction quality is supplier-claimed until independently sampled on agreed documents.

Methodology · How verification works

Companies and providers

Claimed suppliers appear first so buyers can start with listings the company has taken ownership of. Payment does not buy this order.

  • ABBYY

    ABBYY helps enterprises gain a complete understanding of their business processes to accelerate digital transformation with a platform enabled with AI, NLP and OCR. ABBYY publishes

  • Amazon Web Services

    Amazon Web Services is Amazon's cloud division selling compute, storage, Bedrock model hosting and related AI infrastructure. Public pages cover regional cloud services for builder

  • Google

    Google is a US technology company that sells consumer and cloud AI products, including Gemini, Search, and related developer APIs on Google Cloud. Google publishes Imagen, Gemini f

  • Klippa

    Klippa publishes Klippa DocHorizon as named AI products. Klippa is used for Data extraction work. Klippa is recorded in Netherlands. Klippa publishes product information at klippa.

  • LlamaIndex

    LlamaIndex publishes LlamaExtract, LlamaCloud, and LlamaParse as named AI products. LlamaIndex is used for RAG systems and AI SDKs work. LlamaIndex publishes product information at

  • Mindee

    Transform your document workflows with Mindee's AI-powered data extraction APIs. Automate data capture from invoices, receipts, IDs, and more with industry-leading accuracy an

  • Ocrolus

    Ocrolus empowers lenders with accurate data, faster decisions and industry-specific intelligence to automate your workflows. Ocrolus publishes Ocrolus Capture and Ocrolus Analyze a

  • Parseur

    Parseur is an AI data extraction software that helps you automate text extraction from PDFs, emails, and other documents. Instantly send extracted data to all your applications. Pa

  • Reducto

    Reducto is the agentic document platform for leading AI teams—a comprehensive toolkit for every document task, built for enterprise performance at scale. Reducto is used for Data e

  • Sensible

    Extract structured data from any document. Schema-validated, traced to source coordinates, scored for confidence. Sensible Technologies, Inc..so, Data extraction. Sensible is recor

  • Unstructured

    Transform complex, unstructured data into clean, AI-ready inputs. Connect to any source, process 64+ file types, and power your GenAI projects. Unstructured publishes Unstructured

  • Veryfi

    Documents into Data — securely, in seconds. APIs, Agents & SDKs powered by Veryfi AI, enabling multimodal document extraction, fraud detection, and endless business use cases. Very

Products

Claimed products appear first. Ranking packs and payment do not change this list.

Also used in this category

These products have a different primary category so they do not compete for the same ranking queries. They are listed here because buyers still encounter them in this job.

Related categories

Relevant procurement and assurance guides

Frequently asked questions

Is this the same as Document AI?

Related. Extraction is schema-first. Document AI may also classify and summarise without a buyer-defined schema.

What is Data extraction?

Data extraction products pull defined fields from documents, emails or web sources into structured records. Unlike general Document AI, the buyer usually brings a schema. The assurance question is field-level accuracy and how source files are stored.

What should buyers ask about AI data retention and deletion?

Establish how long prompts, files, traces and embeddings are kept, who can access them, and how deletion is evidenced. Retention in a debug or eval store can outlast the customer contract if it is not in scope.

How can buyers tell whether customer data is used to train models?

Ask whether prompts, files, logs or outputs are used to train, fine-tune or evaluate models, including by subprocessors. Require the contractual default, any opt-out, and whether the setting can be changed silently. Treat marketing 'we do not train' claims as unverified until evidenced.

What model or provider changes should a buyer insist on being told about?

Material change usually includes a new model family, new region, new subprocessor, new write-capable tool, or a change that affects logging, privacy or human oversight. Those changes should trigger evidence refresh rather than a silent release.

How should buyers verify where AI customer data is processed?

Ask for the named processing locations, cloud regions and any subprocessors that see prompts, files or outputs. A directory listing is not evidence of residency. Independent assessment records the locations that were in scope on the assessment date.

Does a TrustMark on one product cover the rest of the company?

No. Independent assessment is scoped to the named organisation and, where relevant, the named product. Category pages list suppliers as a topic label. They do not imply that every listed company has been assessed.

What incident-handling evidence is useful for AI suppliers?

Buyers should see how AI-specific failures are detected, contained and notified — including unsafe outputs, data leakage and unauthorised agent actions. An incident policy that never mentions models, prompts or tools is incomplete for this class of product.