AI Portfolio ManagementAgent

Constructing an optimal allocation is weeks of modelling assumptions, testing scenarios, and weighing constraints while the committee waits. An AI Portfolio Management Agent runs that construction and optimization against your mandate. It builds the options; the PM decides.

Tecla builds it inside your environment and runs it, wired into the market data, optimization models, and mandate constraints your team already uses.

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The shift underway

Portfolio construction is shifting from static, mean-variance models to AI that tests thousands of scenarios, while managers deliberately keep the allocation decision human. The numbers show the shift and the line.

$150k–750k

typical due diligence spend on a mid-market deal, most of it analyst review time.

Source: DataRooms.org, 2026

100+ hrs

a week analysts work during live deals, much of it organizing and validating data.

Source: Keye PE research

25–35%

less adviser time on a deal when review is AI-assisted in a structured data room.

Source:

How it works

How the agent works

Diligence is reading a data room end to end against a checklist, then writing up what matters, exacting work done under deal-clock pressure. The agent does that reading for every document and drafts the findings, so the deal team starts from a memo, not a pile of PDFs.

01

Data Room Read

Ingests the full data room, financials, contracts, cap table, corporate records, and reads every document rather than sampling, so nothing material is missed under deadline.

Reads the room
02

Checklist Runner

Works the diligence checklist your firm uses, mapping each requested item to what the data room actually contains and flagging what is missing.

Works the checklist
03

Risk Finder

Surfaces what deals turn on: customer concentration, change-of-control clauses, revenue-recognition issues, unrecorded liabilities, and off-checklist red flags.

Finds the risk
04

Source Linker

Ties every finding back to the exact document and page it came from, so an analyst can verify each point before it reaches the investment committee.

Cites the source
05

Memo Draft

Assembles the findings into a draft diligence memo in your firm's own template and format, ready for the deal team to refine and present.

Drafts the memo

Human in the loop

Every finding traces back to the document it came from, so an analyst can verify each point. The agent reads and drafts; the investment decision, and the judgment on what a red flag means for the deal, stays with the deal team, not the model.

Scoped to you

This is a typical due diligence build. The exact parts are scoped to how your firm runs: your diligence checklist, which workstreams the agent covers, your memo template, and how findings route to the deal team.

See what this would look like built around your portfolio operation.
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Related agents

How it reaches production

Built, run, and owned, one phase at a time

A diligence tool that reads a clean sample can still miss what matters in a real, messy data room under deal-clock pressure. A scoped brief, a named team, and someone accountable at each stage are what make this one dependable on live deals.

Sprint

Scope, fixed price

We map your diligence checklist, the workstreams in scope, your memo template, and the data room setup, then return a plan and a price before you commit.

AI Solutions Lead
Build

Built into your environment

Senior engineers assemble the agent inside your environment, wired into the data room, deal management, and document systems your team already works in.

AI Systems Lead
Run

Monitored and improved

The agent adapts as your checklist and deal types change, and we report against the metrics set at scope: documents reviewed, diligence turnaround, findings surfaced per deal.

Systems Lead + Engineers
Own

Yours, improving

The system is yours to keep, and it learns your firm's diligence standards over time rather than staying a generic document reader bolted on the side.

Your team

A build starts with a fixed-price Tecla Sprint that scopes and prices it before you commit.

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How it holds up

Trustworthy enough to put in front of the IC

A diligence finding the deal team cannot trust is worse than none, because the investment decision rests on it. What makes this one dependable is that every finding is sourced to the document, checkable, and stops short of the investment judgment that belongs to a person.

Reviewed by trajectory

Every finding cites the document

Each finding links back to the exact document and page in the data room, so an analyst can verify it before it reaches the investment committee. The agent surfaces; it does not assert what it cannot source.

Human in the loop

It reads, the deal team decides

The agent reads documents and flags risks, but what a finding means for the investment, and whether to proceed, stays with the deal team. It informs the decision; it does not make it.

Tuned over time

It learns your diligence standard

As your checklist, memo format, and deal types change, the agent is kept current, so its output matches how your firm actually runs diligence.

Start the build

Build the allocations, keep the decision

A scoping call maps your diligence workflow and returns what the agent would handle, how success is measured, and the fixed-price Sprint to build it.

Talk to us

Fixed-price AI Systems Sprint. No commitment until scope is confirmed.

What deal teams ask first

What is an AI portfolio management agent?

It constructs and optimizes candidate allocations against your mandate, refreshes assumptions, applies constraints, stress-tests results, and ranks options for the PM.

How is an AI portfolio management agent different from an optimizer or an OMS?

An optimizer gives one model answer and an OMS executes trades; the agent runs the full construction cycle across methods, constraints, and scenarios.

Does the portfolio management agent decide the allocation?

No. It constructs and stress-tests candidates; the PM makes the allocation decision.

How does the agent handle mandate and IPS constraints?

It applies limits, exclusions, liquidity, and turnover constraints to every candidate so allocations remain investable.

Can the PM see the reasoning behind each allocation?

Yes. Each candidate shows its assumptions, constraints, and stress results so the PM can interrogate the math.

What does Tecla's portfolio management build cover?

Tecla scopes methods, assumptions, mandate and IPS constraints, and risk framework inside your environment.

How is our data and methodology kept secure?

Models, assumptions, and portfolio data remain in your environment under your access rules.

How long does a portfolio management build take?

A fixed-price Sprint maps methods, assumptions, and constraints before the build.

We have a quant and PM team already. Where does the agent fit?

It runs the modelling cycle so quant and PM teams focus on the allocation decision and mandate.

How do we get started with Tecla?

A scoping call maps the construction workflow and returns scope, success measures, and Sprint cost.

Have any questions?
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