Hallucination detection companies, products & suppliers
Checking whether generated claims are supported by sources or known facts. Jobs: faithfulness checks; claim verification; abstention triggers.
What is Hallucination detection?
Checking whether generated claims are supported by sources or known facts. Jobs: faithfulness checks; claim verification; abstention triggers.
What problems does it solve?
Fluent answers still contain unsupported facts.
Typical business use cases
- Faithfulness checks
- Claim verification
- Abstention triggers
Important capabilities
- Claim extraction
- Source alignment
- Scores
What buyers should evaluate
- What counts as a source
- Latency
- False accusations of hallucination
Risks and governance considerations
A detector that blocks true answers or lets invented citations through.
Procurement checklist
- Method
- Source policy
- Human appeal
Relevant AI Trustmark assurance
AI Trustmark independent findings appear only when an assessment or certificate exists. Category membership does not imply verification.
Products and providers
Open a product profile for its catalogue details, or use the provider link for the company profile. Claimed listings appear first, then by name. Payment never changes the order.
By Arthur
One control plane for trustworthy enterprise AI — performance, observability, guardrails, and governance across the full lifecycle. Arthur Bench is Arthur's software product, from
By Cleanlab
Cleanlab helps teams build safer AI agents by preventing incorrect responses from reaching users. Detect and remediate incorrect responses from any AI agent to ensure safety, compl
By Deepchecks
Deepchecks LLM Evaluation is Deepchecks's software product, from Deepchecks Ltd. Published at deepchecks.com/llm-evaluation. Directory filing: Hallucination detection. Vendor legal
By Evidently AI
Ensure your AI is production-ready. Test LLMs and monitor performance across AI applications, RAG systems, and multi-agent workflows. Open-source. Evidently is Evidently AI's softw
By Patronus AI
Patronus AI develops simulation research and infrastructure to accelerate progress toward human-aligned AGI. Lynx is Patronus AI's model API, from Patronus AI, Inc. Published at hu
By Ragas
Ragas is an open source framework for testing and evaluating LLM applications. Ragas provides metrics , synthetic test data generation and workflows for ensuring the quality of you
By Splunk
Unify security and observability at petabyte scale on the Splunk data platform for trusted AI. Stop threats and prevent downtime at machine speed. Luna Evaluation Models is Splunk'
By Vectara
Hughes Hallucination Evaluation Model is Vectara's model API, from Vectara, Inc. Published at huggingface.co/vectara/hallucination_evaluation_model. Directory filing: Hallucination
Products
Claimed products appear first. Ranking packs and payment do not change this list.
- Arthur Bench· Arthur
- Deepchecks LLM Evaluation· Deepchecks
- Evidently· Evidently AI
- Hughes Hallucination Evaluation Model· Vectara
- Luna Evaluation Models· Splunk
- Lynx· Patronus AI
- Patronus AI Evaluator· Patronus AI
- Ragas· Ragas
- Splunk Agent Observability· Splunk
- Trustworthy Language Model· Cleanlab
Related categories
Relevant procurement and assurance guides
Frequently asked questions
What is Hallucination detection?
Checking whether generated claims are supported by sources or known facts. Jobs: faithfulness checks; claim verification; abstention triggers.
What should not be listed as Hallucination detection?
Products whose buyer job is content moderation, RAG products, or eval platforms. Those belong on their own category page so search queries are not split.
Has AI Trustmark independently assessed every Hallucination detection supplier?
No. A category listing is descriptive. Independent assessment is shown only on company or product pages that carry Trustmark evidence.
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.
How should prompt injection and tool-output attacks be controlled?
Agents that read untrusted content or tool output can be instructed to exfiltrate data or take writes. Buyers should ask what is treated as untrusted, whether tool output can change the plan, and what tests were run. Scanner marketing is not the same as independent testing.
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.