Retrieval infrastructure companies, products & suppliers

Pipelines that chunk, index and fetch context for applications, not the database alone. Jobs: chunking pipelines; hybrid retrieval; context assembly for apps.

What is Retrieval infrastructure?

Pipelines that chunk, index and fetch context for applications, not the database alone. Jobs: chunking pipelines; hybrid retrieval; context assembly for apps.

What problems does it solve?

Each app reinvents chunking, connectors and fetch policies.

Typical business use cases

  • Chunking pipelines
  • Hybrid retrieval
  • Context assembly for apps

Important capabilities

  • Connectors
  • Chunk policy
  • Fetch APIs

What buyers should evaluate

  • Chunk leakage across ACLs
  • Freshness
  • Who owns the pipeline

Risks and governance considerations

A shared retriever that ignores document permissions.

Procurement checklist

  • ACL tests
  • Freshness SLA
  • Pipeline ownership

Relevant AI Trustmark assurance

AI Trustmark independent findings appear only when an assessment or certificate exists. Category membership does not imply verification.

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.

  • Cohere

    Cohere is a Toronto-headquartered model company selling text, embed and RAG-oriented APIs for enterprises. Public pages emphasise private deployment options alongside hosted APIs.

  • Contextual AI

    Replace DIY complexity with the context engineering platform built for accuracy. Ship production-grade AI that is secure, scalable, and specialized. Contextual AI publishes Context

  • deepset

    Build agents and RAG systems using the Haystack Enterprise Platform, trusted by enterprise, defense, and regulated industries. deepset publishes deepset AI Platform as named AI pro

  • Elastic

    Power insights and outcomes with The Elasticsearch Platform. See into your data and find answers that matter with enterprise solutions designed to help you accelerate time to insig

  • Jina AI

    Embeddings, rerankers, web reader, deepsearch, small language models. Jina AI publishes Jina Reader API and Jina Reranker API as named AI products. Jina AI is used for Retrieval in

  • Microsoft

    Microsoft Corporation sells Windows, Azure, Microsoft 365 and Copilot AI products. Public pages cover cloud, productivity and developer APIs used by enterprises and consumers. Micr

  • Mixedbread

    Make your agents work on your data. Mixedbread turns PDFs, decks, videos, code, Slack, and Drive into evidence your agent can act on, with fewer tokens. Mixedbread publishes Wholem

  • MongoDB

    Get your ideas to market faster with a flexible, AI-ready database. MongoDB publishes MongoDB Embedding and Reranking API as named AI products. MongoDB is used for Retrieval infras

  • Pinecone

    Pinecone is the trusted AI knowledge company. Its AI knowledge platform—Database, Nexus, and Marketplace—powers accurate, fast, cost-effective AI for 10,000+ customers and 1M devel

  • Weaviate

    Bring AI-native applications to life with less hallucination, data leakage, and vendor lock-in. Weaviate is used for Retrieval infrastructure and Vector databases work. Weaviate is

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

What is Retrieval infrastructure?

Pipelines that chunk, index and fetch context for applications, not the database alone. Jobs: chunking pipelines; hybrid retrieval; context assembly for apps.

What should not be listed as Retrieval infrastructure?

Products whose buyer job is vector databases, RAG product UIs, or enterprise search. Those belong on their own category page so search queries are not split.

Has AI Trustmark independently assessed every Retrieval infrastructure supplier?

No. A category listing is descriptive. Independent assessment is shown only on company or product pages that carry Trustmark evidence.

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.

What security testing evidence should buyers request for an AI product?

Ask what was tested, against which version, whether prompt-injection, data-exfiltration and tenant isolation were in scope, and where failed prompts were stored. A generic ISO certificate or a vendor scanner screenshot is not by itself an AI TrustMark assessment.