Asset & Investment Management
Let your analysts analyse.
Asset and investment managers pay for judgement and get transcription. An hour per company re-keying broker research, half a day assembling a workbook before any thinking begins. AI agents do the mechanical half — reading the research, building the model, watching the language shift across an entire portfolio — so the analyst gets to the part you actually hired them for.
What we hear
- An hour per company spent copying numbers out of broker reports
- Half a day building the workbook before any thinking begins
- Tone shifting in company commentary before it shows up in the numbers
- Research and CRM logging that quietly never gets done
Agents built for Asset & Investment Management
Each one says how it works, what it connects to, and where it was built.
Meeting Preparation Agent
Walks into every meeting knowing what happened in the last one.
A Meeting Preparation Agent reads the next two days of your calendar, matches every attendee against your CRM, and gathers what your teams have said internally alongside what the market has said publicly — then emails a structured briefing before the day starts. It runs daily, without being asked.
Daily Briefing Agent
What you need to know, before anyone asks you about it.
A Daily Briefing Agent assembles what changed overnight across the systems and sources you care about, and delivers one briefing before the working day starts — so the first meeting is not the first you hear of it.
Economic & Market Insight Agent
The rate decision, read and summarised, before the meeting about it.
An Economic & Market Insight Agent watches the economic releases and market data that move your business — central bank decisions, housing figures, the numbers your customers read — and summarises what changed and what it means for you.
Broker Research Extraction Agent
Reads the broker report so the analyst does not have to re-key it.
A Broker Research Extraction Agent reads incoming broker research and pulls the figures straight into the financial model — removing the hour of manual transcription that stands between a report arriving and an analyst being able to think about it.
Financial Workbook Builder Agent
Builds the three-statement model from the filings.
A Financial Workbook Builder Agent reads a company's reported financials and assembles a working three-statement model — the task an analyst described as taking three to four hours, done while they read the commentary.
Tone & Sentiment Shift Agent
Notices the language changed, before the market does.
A Tone & Sentiment Shift Agent compares how a company talks about itself now against how it talked six months ago, and flags the negative shift in language in a results presentation — before the market opens.
What we have done here
We have prototyped research extraction, workbook building and sentiment-shift agents for a listed Australian asset manager, including a live demonstration of a task the team said took three to four hours.
Asset & Investment Management questions
How can AI agents help an asset or investment manager?
They take the mechanical half of the analyst's day. Reading broker research and populating the model rather than re-keying it by hand. Building a three-statement workbook from filings. Watching how a company's language shifts across an entire portfolio and flagging it before market open. The analyst gets to the judgement you actually hired them for.
What if an agent misreads a figure in a financial model?
It says so explicitly rather than guessing. An agent that silently invents a number is worse than no agent at all, particularly inside a model somebody is going to act on. Anything it could not read with confidence is flagged for a human.
How much analyst time does this actually save?
Extracting broker research removes roughly an hour of manual entry per company covered. Building a three-statement workbook replaces a task one team described as taking three to four hours. Across a portfolio, that compounds into days a month.
Do we have to replace our existing tools?
No. Agents read from and write into the systems you already use — your research providers, your models, your CRM. Proposing a migration before delivering any value is a good way to spend a year and prove nothing.
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