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Asset management & finance

AI for financial firms & asset management

Reporting, regulatory summaries, note preparation, regulatory monitoring. AI agents for an industry where documentary rigour and compliance reign.

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Concrete use cases

What AI can automate for you

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Automated reporting

Generating periodic reports from your data, formatted to your house style.

Reports produced faster
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Regulatory summaries

Summarising long regulatory documents (prospectuses, KIDs, regulator texts) into actionable points.

Regulatory reading pre-digested
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Note preparation

First drafts of research notes, committee papers and investment memos, sourced from your data.

The analyst refines, AI does the legwork
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Regulatory monitoring

Tracking regulatory and market developments, with sourced and dated summaries.

No regulatory change missed
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Document extraction

Extracting data from large financial documents, with filing and indexing.

Instant document search
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Q&A on your documents

An agent answers your teams' questions by drawing on your own document bases.

Internal knowledge made accessible

An industry that runs on documents

Asset management and finance produce and consume mountains of documents: reports, prospectuses, notes, regulatory texts. It is an ideal field for AI agents that can read, summarise, extract and draft — always under human control.

Compliance at the core

Pseudonymised data, France / EU hosting, source traceability. Agents cite the documents they rely on: no untethered answers, verifiable summaries. Regulatory and GDPR compliance are built in from the design stage.

Custom, integrated, in production

Every firm has its own processes and reference data. We design agents calibrated to yours, integrated with your tools, deployed in production — not prototypes.

AI software for finance

“AI software” doesn't mean another generic tool. We build artificial intelligence for finance, custom and integrated into your own tools: your AI software for finance, designed for your field — not a standard SaaS you have to work around.

FAQ

Your questions about AI in your profession

What is an AI agent in asset management?
It is a specialised analysis tool for financial firms. It automates the summarisation of large volumes of information, such as regulatory reports (from bodies like the FCA, ESMA), market analyses, or company earnings reports. It prepares summaries and identifies key trends to support decision-making by managers and analysts.
How does the AI guarantee trade secrets and the confidentiality of strategies?
The system operates within a private and highly secure infrastructure. Proprietary data, analyses, and investment strategies are processed in a dedicated and isolated environment. There is no data pooling, and the models are not trained on client information, guaranteeing complete confidentiality.
Is the data hosting sovereign and compliant with financial regulations?
Yes. The data is hosted on servers in the European Union, often in France, to ensure data sovereignty. The platform is designed to meet the strict requirements of GDPR and the financial sector, providing a secure and compliant framework for processing sensitive information.
What is the performance gain for an analyst team?
The main benefit is the acceleration of the research and analysis process. An AI agent can monitor thousands of sources and produce concise summaries in real time. This allows analysts to cover a wider range of assets or regulations and dedicate more time to strategic analysis rather than data collection.
Can the AI interface with our financial terminals (e.g., Bloomberg, Reuters)?
AI agents can be integrated with various data sources. Via APIs, they can be connected to financial data feeds, internal databases, or market analysis tools to enrich their analyses. The objective is to centralise information and make it immediately actionable within the existing workflow.
How can we ensure the AI's summaries are not biased or incorrect?
Reliability is ensured by a RAG (Retrieval-Augmented Generation) approach. The AI's summaries are based exclusively on a defined and verifiable set of source documents (official reports, financial news wires). Each piece of generated information is traceable to its source, allowing the analyst to quickly verify its accuracy. The human expert remains the final validator.
Where should an asset management firm start? A practical example?
A powerful use case is regulatory monitoring. Configure the agent to monitor all publications from regulators (e.g., FCA, ESMA). Ask it to:
  • Detect any new directive concerning a specific asset class.
  • Summarise the potential impacts on your portfolios.
  • Generate an email alert for the compliance team with a summary and a link to the official source.
This automates a critical and time-consuming monitoring task.

A time-consuming workflow in mind?

30 minutes to pinpoint what AI can save you. No commitment, no jargon.

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