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AI Blueprint · Investment Banking, Corporate Finance & Credit

Discover where AI agents can increase execution capacity across investment banking, corporate finance and credit

I help investment banking, corporate finance and credit teams map workflows, identify bottlenecks and design AI agents to accelerate origination, research, buyer lists, valuation support, materials, debt analysis, diligence and pipeline management. Lean teams must deliver high-quality work — my job is to understand how your operation works today and design a practical plan to use AI where it truly creates leverage.

I do not start with the tool.I start by understanding how your operation works today.

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Fernando Martignone Esteves

Who it is for

Independent financial advisory boutiques and firms in investment banking, corporate finance and credit — especially middle market, with lean teams and heavy manual production of research, valuation, teasers, CIMs, debt analysis and data rooms.

Workflows we can implement

Workflows that can be mapped through the Blueprint or implemented directly when the use case is already clear.

investment banking, corporate finance and credit teams do not need more AI hype. They need operational leverage.

In a boutique, much of the team's time still goes to manual tasks:

The problem is not lack of knowledge.
It is lack of operational capacity to execute everything with speed and consistency without inflating headcount.

I start by understanding how your boutique executes deals today.

Before talking about tools, I analyze the real operating workflow:

From there, I design an AI Blueprint with the agents that can increase the boutique's execution capacity.

What I review

During the Blueprint, I review the main stages of the M&A operation.

AreaWhat I assess
OriginationHow opportunities are generated, qualified and tracked
ResearchHow companies, sectors, buyers and transactions are researched
Buyer listsHow strategic and financial buyers are mapped
MaterialsHow teasers, one-pagers, profiles and presentations are created
PipelineHow status, follow-ups and next steps are managed
DiligenceHow documents, risks and questions are organized
Q&AHow questions and answers are tracked
DataWhich CRMs, spreadsheets, databases, documents and templates already exist

Example agents that can emerge from the Blueprint

Buyer list agent

Generates an initial list of strategic and financial buyers, with acquisition rationale, potential synergies and outreach priority.

Value: reduces research hours and helps the team start with a more structured list.

Company profile agent

Creates company profiles with business description, market, revenue model, competitors, risks and meeting questions.

Value: speeds up preparation for calls, meetings and initial analysis.

Sector research agent

Summarizes market trends, growth drivers, relevant players, recent transactions and themes that support the thesis.

Value: improves material quality and reduces manual research.

Pipeline and follow-up agent

Organizes buyer status, next steps, pending messages and follow-up recommendations.

Value: avoids missed timing and improves commercial discipline.

Materials preparation agent

Supports creation of teasers, one-pagers, buyer rationale, outreach emails and executive summaries.

Value: reduces time between opportunity and material ready for review.

Initial diligence agent

Reads documents sent by the client and extracts risks, inconsistencies, open items and questions for management.

Value: helps the boutique anticipate issues before taking the asset to market.

Q&A agent

Groups similar questions, suggests initial answers and helps maintain consistency during the process.

Value: reduces noise and rework during diligence.

What you receive

At the end of the AI Blueprint, you leave with a clear plan to apply AI in your M&A operation. Deliverables include:

1. Diagnosis of main bottlenecks

An objective view of processes where your firm loses time, relies on manual tasks or has low traceability.

2. AI opportunity map

A clear list of workflows where agents can create real value.

3. Use case prioritization

Ranking of opportunities by impact, complexity, risk, data dependency and implementation speed.

4. Blueprint of recommended agents

For each priority agent, I design:

  • objective;
  • end user;
  • required inputs;
  • expected outputs;
  • data sources;
  • business rules;
  • human controls;
  • risks;
  • success metrics.

5. Implementation roadmap

A practical plan to move from diagnosis to quick wins, pilot and scale.

6. Build vs buy recommendation

Guidance on what makes sense to build, buy, customize or integrate.

7. Risks and governance

Attention points on privacy, governance, suitability, traceability, human review and data security.

A founder-led diagnostic tailored to your boutique

I personally lead the Blueprint with partners and/or execution leads.

Typically, the project runs over 4 weeks. The format adapts to your operation: sell-side, buy-side, capital raises, corporate finance, lower middle market or strategic advisory.

The goal is not a generic AI presentation. It is to turn your current operation into a practical plan to increase execution capacity with agents.

Before and after

Exemplo: buyer list

Before

The analyst researches buyers manually, builds a spreadsheet, writes rationale buyer by buyer and updates status by email.

After

An agent generates the initial buyer universe, classifies buyers by strategic fit, suggests acquisition rationale, drafts outreach and organizes status for banker review.

Exemplo: company profile

Before

The team spends hours gathering public information, client materials, sector data and meeting notes.

After

An agent generates a first draft company profile with description, market, competitors, risks, potential buyers and questions for deeper review.

Exemplo: initial diligence

Before

The team reviews documents manually and finds inconsistencies too late.

After

An agent flags open items, risks, questions for management and points that may affect valuation or process narrative.

In M&A, speed and consistency become competitive advantage.

A boutique that uses AI only to “summarize text” gains little. A boutique that redesigns workflows with agents can:

Implementação

The Blueprint does not require you to implement with AIQGEN. Agent implementation can be led by AIQGEN afterward, but it is optional and scoped separately.

The Blueprint goal is to help you decide clearly:

Fernando Martignone Esteves

Who leads this

Led by Fernando Martignone Esteves

I am founder of AIQGEN.

Before da AIQGEN, atuei por mais de 10 anos no Itaú BBA em corporate banking, estratégia, pricing e AI/ML, com experiência em análise de clientes, recomendação de produtos, eficiência comercial e tomada de decisão em ambientes regulados.

In this Blueprint, my role is to help your boutique turn AI into practical leverage: fewer manual tasks, faster execution and more time for relationships, negotiation and closing.

LinkedIn View resume

Blueprint format

AI Blueprint Founder-Led

Duration: 4 weeks

I personally lead a diagnostic of your operation to identify where AI agents can create real value and deliver a practical implementation blueprint.

  • diagnosis of current bottlenecks;
  • AI opportunity map;
  • use case prioritization;
  • design of recommended agents;
  • implementation roadmap;
  • risk and dependency analysis;
  • tooling and architecture recommendation;
  • final executive presentation.

Agent implementation, integrations or customizations are not included. They can be led by AIQGEN in a follow-on phase with a separate proposal.

Discover where AI can increase your boutique's execution capacity.

Schedule a conversation to see if the AI Blueprint fits your operation.

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Contact us
João da AIQGEN

João da AIQGEN

Financial AI Consultant • Online

Hello! I specialize in AI agents for financial firms. How can I help you today?