AlphaSense

AlphaSense

AlphaSense searches earnings calls, broker research, filings, and company material.

Oximy ResearchUpdated 19 September 2026

Overview

A+
Transparency
3 / 10
Trust
96 / 100

Trains on your data

Free
No
Paid
No
Opt-out
Not captured

Incidents

0

0

Assessed SEP 21, 2026 · Checked by hand SEP 21, 2026

SOC 2, ISO 27001, GDPR DPA, no customer-content model training, provider zero retention and US and EU hosting are confirmed; the unconfirmed breach commentary was removed.

Trust breakdown

A+

96 / 100

Overall trust score

Data safetyComplianceIncidentsLegal
Data safety100
Compliance92
Incidents100
Legal87

Data and privacy

Trains on your data

No training on user data

Storage regions

United StatesGermany

Sub-processors

Not disclosed

Data retention

We work exclusively with LLM vendors who adhere to a strict zero data retention policy.

Deletion: Upon termination of this Agreement for any reason, the receiving party shall promptly return or destroy (at the disclosing party's option), all copies of the other party's Confidential Information.

Powered by

Anthropic's Sonnet 4 familyGoogle's Gemini 2.5OpenAI's o3GPT-5.6 SolKimi K3Opus 5Opus 4.8Gemma 4
Proprietary model

AlphaSense uses a proprietary platform that acts as an intelligent orchestrator, dynamically leveraging and combining leading reasoning models from third-party providers (Anthropic, Google, OpenAI) with their own high-value content and search technology. They also utilize classical machine learning models for tasks like entity recognition and sentiment scoring, and have developed their own 'Context Graph' and 'AlphaSense Search' technology.

Integrations and access

Integrations

API: Yes

Available on

Web
iOS
Android
macOS
Windows
Linux
Extension
CLI

Pricing

Enterprise

Custom

AlphaSense does not publicly disclose pricing. They offer flexible subscription options, including enterprise-wide solutions and per-seat pricing, tailored to an organization's needs. Pricing is structured around per-seat licenses with tiered access to content libraries. Final costs depend on seat count, content depth (standard vs. premium), contract term (annual vs. multi-year), and optional services like expert interviews or premium data feeds. All contracts are negotiated directly with the sales team. They offer two main packages: Market Intelligence and Enterprise Intelligence. Enterprise Intelligence includes everything in the Market Intelligence package plus AI search and summarization on internal content, additional cloud-hosting options, API uploads, and customized training and IT support. Add-ons include Expert Calls and Canalyst financial models. Based on verified 2026 contract data, average SMB pricing is $44,754 per year, and average enterprise pricing is $125,124 per year. Enterprise deals can exceed this. A UK public contract for 13 users was £81,900 a year, which breaks down to £6,300 per named user per year. Vendr's brokered median across 38 purchases is $17,500, ranging from $9,250 to $51,000 (total contract value).

Prices as listed on SEP 21, 2026; check the vendor's page.

Moat and openness

7/ 10
Moat 7 out of 10

Moat

  • Proprietary Model
  • Proprietary Data
  • Network Effects
  • Switching Costhigh
  • Unique UX
  • Distributionstrong

AlphaSense exhibits a strong moat primarily due to its proprietary platform orchestrating leading AI models with its vast, high-value content library and specialized search technology. The deep integration into enterprise workflows, high switching costs associated with data migration and retraining, and strong distribution to Fortune 500 companies further solidify its defensibility.

5/ 10
Openness 5 out of 10

Openness

  • Open model weights
  • Published research
  • Open source contributions
  • Transparency reports
  • Public safety evals

AlphaSense demonstrates moderate openness, particularly regarding its data handling and security practices. It explicitly states that customer content is not used to train its models or third-party LLMs, and it works with LLM vendors who adhere to a zero data retention policy. Data is encrypted, and dedicated storage environments are provided for each customer. AlphaSense also emphasizes auditability and provides citations for AI-generated insights, allowing users to verify information. However, the company is less transparent in other areas, such as breach notification, specific data retention periods, and clear affirmation of customer ownership of AI outputs. There is no indication of open model weights, published research, open-source contributions, transparency reports, or public safety evaluations.

Timeline

  1. 2024-09AlphaSense acquired Tegus for $930M, integrating Tegus's archive of 150,000 expert-call transcripts into the AlphaSense corpus to enhance its generative AI capabilities.
  2. 2023-06AlphaSense launched Generative Search, an AI-powered conversational search tool built on its existing Smart Synonyms search infrastructure. It provides citation-backed answers from its licensed research corpus.

Company

AlphaSense

Founded
2011
HQ
New York, NY, US

Popularity

Not disclosed

monthly visits

Notable customers

AdobeAmazonAmerican ExpressCiscoThe D. E. Shaw GroupJ.P. Morgan Chase & Co.Microsoft CorporationNetAppNestléNvidiaPfizerSalesforceSingtelEmirates NBDOricaBDO USASoliciYH2 CapitalODDO BHFGalapagosTheramexCardinal HealthUBSUnilever

AlphaSense is an AI-powered market intelligence platform that helps professionals find and analyze business information across millions of documents, serving over 7,000 global enterprises including a majority of Fortune 500 companies and nearly all of the world’s largest financial institutions.

Value and ROI

What it should move: Analysts spend less time researching and preparing forecasts, earnings material, and peer analysis.

Best fit

It fits teams that need cited market research across many licensed documents.

The catch

Access depends on licences and entitlements. Analysts must verify context, dates, and forecast assumptions.

  • Fresenius Group: Uses AlphaSense to follow market sentiment, competitors, broker research and earnings statements.[1]
  • System1: Uses AlphaSense for peer earnings analysis, internal projections and industry research.[2]

In our stacks for

References