Great feedback, Shane. From my (admittedly small) sample, adoption still seems early. Large firms are experimenting with tools like Claude Enterprise, but broader rollout in financial services - especially among mid- and small-size firms - will likely be slower due to compliance, data licensing, auditability, and workflow integration.
Most of the projects I've worked on for smaller firms have been fairly straightforward: using open-source models with finance-specific training, then fine-tuning them on the client's proprietary data to automate specific time-consuming tasks. So far none of those clients have wanted to go the Claude route, mainly because of cost and because these lighter open source solutions already deliver meaningful productivity gains. Curious to hear the experience of others in the community.
In that sense, Claude isn't really a standalone solution yet because of the data component you highlighted. The pricing ranges you mentioned sound plausible, but the comparison isn't apples-to-apples. Seats may appear cheaper, but once you add licensed datasets, APIs, governance, and integration, the total enterprise cost can increase quickly. The real decision for firms is likely AI layer + data stack, not AI versus platforms like Bloomberg or FactSet.
More broadly, it reminds me of where things were in 2023. It feels like we're now closer to the trough of the hype cycle for LLMs after the early-2023 peak, with practical LLM workflows likely to become common over the next couple of years. Agents, on the other hand, still feel firmly in the hype phase-we probably need a few reality checks and more maturity in LLM workflows before they're widely implemented across small, mid, and large financial firms.
Once again, happy to hear more voices in the community providing additional info as my sample is rather small as I said.
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Carlos Salas
Portfolio Manager & Freelance Investment Research Consultant
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Original Message:
Sent: 08-03-2026 10:34
From: Shane Jocelyn
Subject: Cowork and plugins for teams across the enterprise - latest release from Anthropic
Thanks Todor for highlighting. I would love to see this in action. Currently only available with Claude Enterprise but I wonder how many firms are adopting and how long it will take for the mainstream to adopt their own tools.
I also am curious how many of the traditional firms are going to be launching their own AI models or at least something that leverages these tools. For example, FactSet and Bloomberg are seemingly taking two different paths from what I can understand with the former embedding foundational models and the latter trying to develop their own learning models. To what degree are they going to be disintermediated? FactSet share price -50% in the last year suggests the market believes buyers are going to be straight to Claude Enterprise.
How competitive is pricing? I was interested to learn the below knowing the expense of a single license with FactSet or Bloomberg. It would seem to be significantly cheaper but then Claude Enterprise doesn't appear to have the data warehouse of the traditional financial platform providers?
What do we know about ballpark costs?
Anthropic doesn't publish Enterprise seat prices publicly, but third-party analysis suggests Enterprise plans typically start around $500–$1,000/month for small deployments of 10–25 users, scaling to $5,000–$15,000+/month for large organisations of 100+ users with custom usage guarantees. There's also a minimum of 20 seats required with an annual commitment.
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Shane Jocelyn
Director
Original Message:
Sent: 01-03-2026 22:12
From: Todor Kostov
Subject: Cowork and plugins for teams across the enterprise - latest release from Anthropic
Link to the update below.
Claude Cowork
New connectors and plugins:
- HR: Support people operations across the employee lifecycle, from drafting offer letters and building onboarding plans to writing performance reviews and running compensation analyses.
- Design: Accelerate design workflows by generating critique frameworks, drafting UX copy, running accessibility audits, and structuring user research plans.
- Engineering: Streamline day-to-day engineering workflows like writing standup summaries, coordinating incident response, building deploy checklists, and drafting postmortems.
- Operation: Manage core business operations including process documentation, vendor evaluations, change request tracking, and runbook creation.
- Brand voice (by Tribe AI): Analyze your existing documents, marketing materials, and conversations to distill your brand's voice into clear, enforceable guidelines.
- Financial Analysis: Support the baseline workflows every finance analyst needs, from market and competitive research to financial modeling and PowerPoint template creation and quality checking.
- Investment Banking: Accelerate deal workflows including reviewing transaction documents, building comparable company analyses, and preparing pitch materials.
- Equity Research: Streamline research workflows like parsing earnings transcripts, updating financial models with new guidance, and drafting research notes.
- Private Equity: Support deal sourcing and diligence by reviewing large document sets, extracting standardized financial data, modeling scenarios, and scoring opportunities against investment criteria.
- Wealth Management: Help advisors analyze portfolios, identify drift and tax exposure, and generate rebalancing recommendations at scale.
- Todor
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Todor Kostov
Director
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