LinqAlpha

LinqAlpha has the deepest AI research record in our coverage. Its team has published peer-reviewed work at ICAIF, ACL and EMNLP, released public finance benchmarks, and in 2024 built an embedding model that ranked first for retrieval on the MTEB leaderboard. An AI Lab with a named Chief Scientist followed in August 2026. For buyers who weigh how a system reasons, not only what it shows, this is unusual evidence.

The commercial and platform evidence is earlier. A $22m Series A in July 2026 brought strategic Asian financial investors, and the company reports 70+ paying institutions with 90%+ retention. Native-language coverage of Asian markets is a clear differentiator. We did not locate Office integrations, SSO, a no-training commitment or published pricing, and the company describes private-cloud deployment as a future stage.

We lower the rating to Emerging, at 6.30, with an Improving outlook. This Rating Review applies the full sub-criteria standard used for every company covered since October and replaces the 7.11 published on 20 October. Under that standard, company-reported figures and claims are recorded but do not lift a score, and controls or content not located publicly score low until evidenced. The largest moves are in Enterprise Readiness, now 5.50, where MNPI controls, SSO and a no-training commitment were not located, and in Data & Content, now 5.42, where licensed broker and expert content is absent. AI & Technology, at 7.50, remains the strongest dimension; the published research is peer-reviewed but evaluates models rather than the shipped product. The only material development since our last review is a September memorandum of understanding with KOSCOM, which we treat as a plan rather than live data. The position moves from Innovators to Emerging.

Strengths

• Published research record. Peer-reviewed papers at ICAIF, ACL and EMNLP, public benchmarks (FinAgentBench, FinDER) and an LLM investment-bias leaderboard.
• Retrieval engineering. Its Linq-Embed-Mistral model ranked first for MTEB retrieval in 2024, and the multi-agent architecture is documented in an AWS case study.
• Global native-language coverage. Filings and transcripts across about 120 countries read in their original languages, including Korean DART disclosures back to 2001, and a September 2026 memorandum of understanding with KOSCOM to extend Korean market data.
• Several ways to buy. A Terminal with 50+ agents, a REST API, an MCP server with 22 tools and a data marketplace.
• Strategic investor base. The Series A brought AVP, GFT Ventures and a broad group of Asian financial institutions, giving reach into APAC distribution.
• Retention and logos. The company reports 70+ paying institutions and 90%+ retention; Causeway Capital and Schonfeld are named in company materials.
• Security claims above stage. SOC 1 and SOC 2 Type II and ISO 27001 are claimed, with a Drata-hosted trust portal.

Cautions

• Delivery surfaces. We did not locate Excel, PowerPoint, Teams or Slack integrations.
• Deployment. The company describes VPC and on-premises deployment as a future stage, although an AWS case study describes a VPC architecture.
• Data governance. A zero-data-retention agreement and deletion after use are stated, but a written no-training commitment, SSO/SAML, SCIM, data residency and a subprocessor list were not located.
• Information barriers. No MNPI or information-barrier position was located.
• Content licensing. No licensed broker-research or expert-network feed was located; clients upload their own.
• Inconsistent figures. Client counts range from 70+ to 170+ across materials, and coverage and founding-year figures also vary.
• Scale. The team was about twenty people in January 2026 and is hiring across six offices.
• Pricing. Pricing is not published; contract values are reported at $20,000 to over $200,000 a year.