Samaya AI

Agents automate multi step workflows, monitor markets and generate financial models, reports and presentations, and question answering returns cited answers across filings and broker research. Nothing operable would remain without the models.

Multi step workflows run under agents, and an economic agent produces quantitative predictions through multi stage reasoning without a person directing the steps. Approval gates and review before output reaches research delivered to clients are not described.

Models are purpose built for factuality, and a comparative figure of 96 percent accuracy against 57 percent for GPT based systems concedes that performance should be measured. Its tester, method and question set are unnamed, and model documentation is absent.

Morgan Stanley uses the platform across research, sales and trading and banking, with its global director of research, Katy Huberty, quoted, and more than 10,000 seats are claimed. A top five hedge fund, named only by role, is said to have chosen it after pilots with about 40 vendors.

Custom models are trained and combined with frontier models while the platform stores a major bank's research library, and whether customer documents train either is not stated. What frontier providers receive, and whether anything pools across customers, goes unaddressed.

A privacy policy last modified August 13, 2024 covers the website only, leaving platform data to separate terms. Research libraries and restricted internal notes from banks sit on the platform with no published handling, retention or subprocessor detail.

User level access controls, granular permissions and audit logs sit beside a stated SOC 2 compliance. SOC 2 type, audit period and trust portal details are not given.

Inside a bank's research division the output helps create client insights, which places it near analyst conduct rules on independence, disclosure and supervision. How machine generated content enters that process, and how information barriers hold when one platform serves research, trading and banking, is not explained.

Markets and companies are the subjects, so accuracy governance is the question, and a claim of no hallucinations discourages the checking the product otherwise enables. Where agents degrade, including the economic modeling agent, is left unexplained.

Cited evidence lets an analyst verify a claim before it travels. Clients of the bank receive research shaped by the system without learning it was involved, and the vendor offers no accuracy guarantee or remediation term despite promising no hallucinations.

Proprietary finance specific models combine with frontier models from providers that are never named. Hosting providers, content sources and a subprocessor list are also unpublished.

Filings, broker research and internal notes are ingested, and agents can be reached from ChatGPT, Claude and other applications through model context protocol servers or an API. Those are access routes, and no market data vendor, research system or document repository is named as an integration.

Virtual private cloud or sandboxed deployment with isolated execution is described, with cloud and on premises compatible options, so a bank can keep its documents in an environment it controls. Deployment documentation, hosting region and residency are unstated.

Neither seats, agents nor query volume carry a published price. Structures for a global bank across three divisions and a single hedge fund would normally differ widely.

Sell side research, hedge funds and asset managers are among the named functions inside institutional securities. Commercial and retail banking, lending, payments and insurance are not addressed.