How much did Mako AI raise with this deck?

According to publisher-reported facts from Business Insider, Mako AI raised $1.6M in a Seed round in 2024. The deck itself does not state the amount raised or the terms of the round.

What is Mako AI's primary target market?

The deck specifically targets Private Equity, Asset Management, and Professional Services firms. Slide 4 and Slide 9 emphasize workflows unique to these sectors, such as deal sourcing and data room analysis.

How does Mako AI handle data security?

Security is a central theme of the deck. Slide 8 states that Mako is SOC 2 Type II certified and deploys directly into the client's cloud environment (VPC) to ensure data never leaves the firm's control.

Does the deck show any traction or revenue?

The deck does not list revenue or specific customer names. However, Slide 9 claims that 'top investment firms' are using the platform and that users typically execute 2-5 tasks per day.

What makes Mako different from a standard LLM like ChatGPT?

Slide 7 highlights that Mako is a multi-agent system designed for 'messy internal data.' It uses a specialized knowledge graph and provides inline citations to underlying sources to ensure explainability and trust.

Mako AI Pitch Deck: All 9 Slides + Teardown

See all 9 slides of the Mako AI pitch deck — a 2024 Seed deck — with a slide-by-slide teardown of what the deck does well and where it falls short.

Mako AI's 9-slide seed deck is a masterclass in 'founder-market fit' for the enterprise AI sector. Raising $1.6M in 2024, the company targets the high-stakes world of private equity and professional services. The deck eschews typical growth charts and financial projections, focusing instead on the team's background at Bain and Glean to establish immediate credibility. By positioning the product as a 'secure AI Associate' that lives within a firm's own VPC, Mako addresses the primary objection in high-finance AI adoption: data privacy. While the deck lacks a formal 'Ask' slide or business mode…

Key takeaways

The deck relies heavily on team pedigree, citing experience from Bain's Private Equity Group and Glean's Founding Search Team on Slide 2.
Mako positions itself as an 'AI Associate,' a specific persona that resonates with the hierarchical structure of private equity firms (Slide 4).
Security is the primary value proposition, with Slide 8 highlighting SOC 2 Type II certification and deployment within the client's own VPC.
The product is structured as a three-tier offering: AI Associate, Enterprise Search, and a Knowledge Base (Slide 5).
A 2-minute demo video is embedded on Slide 6 to prove the technical feasibility of drafting complex 5-page analyses.
The deck identifies 8 specific high-value use cases, including data room analysis and customer call synthesis (Slide 9).
Mako claims users typically execute 2-5 tasks per day once onboarded, providing a rare glimpse into engagement metrics (Slide 9).
The deck completely omits a financial 'Ask' slide, market sizing (TAM), and a roadmap for future development.

The Pedigree Play: Mako AI's $1.6M Seed Deck

Mako AI entered the 2024 fundraising market with a lean, 9-slide deck that secured $1.6M in seed funding. In an era where generative AI startups are ubiquitous, Mako chose to differentiate not through broad horizontal utility, but through deep vertical specialization in private equity and asset management. The deck is a study in building trust through institutional credibility and technical security.

Slide 1: The Hook

The title slide is minimalist, featuring the Mako logo and the tagline: "The most secure AI Associate." By leading with security rather than intelligence or speed, Mako immediately addresses the number one barrier to AI adoption in the financial services sector. The branding is professional and understated, fitting the aesthetic of the private equity firms they aim to serve.

Slide 2: The Team (The 'Why Us')

Mako places its team slide second, a strategic move for a seed-stage company where the founders are the primary asset. The slide states: "Our founding team comes from Bain’s Private Equity Group, Glean’s Founding Search Team, and other top AI institutions." It features logos from Bain & Company, Glean, AWS, Stanford, Scale AI, C3.ai, Salesforce, and Berkeley. This slide establishes 'Founder-Market Fit' by showing they understand the domain (Bain PE) and have the technical chops to build the solution (Glean, Scale, C3.ai).

Slide 3: The Problem

The problem statement is concise. It notes that professionals "constantly need to find insights fast, synthesize complex data, and make critical decisions," but are "left manually wrangling information" and "struggling to tap into their firm’s goldmine of institutional knowledge." This identifies the 'data silo' problem common in large investment firms where years of deal history are buried in PDFs and spreadsheets.

Slide 4: The Solution

Slide 4 introduces Mako as the "AI Associate built for Private Equity, Asset Management, & Professional Services." The graphic shows the Mako platform sitting at the center of a firm's tech stack, connecting to logos for Microsoft, Notion, Slack, Salesforce, Box, and Dropbox. It defines the core value as supercharging "information retrieval, analysis, & drafting."

Slide 5: Product Architecture

AI Associate: A conversational interface for searches and heavy analysis. · Enterprise Search and Chat: A tool to uncover buried documents and past deal work. · LLM-powered Knowledge Base: A 'single pane of glass' for institutional knowledge.

This structure suggests a comprehensive platform rather than a single-feature tool.

Slide 6: The Demo

Slide 6 is a placeholder for a "2-minute demo video." The static image shows the AI Associate drafting a 5-page analysis on a company called 'RevMax,' using a 'Keyflow 5-Pager' as a reference. The UI displays a step-by-step plan including 'Document search,' 'Pick reference examples,' and 'Build outline.' This transparency into the AI's reasoning process is critical for building user trust in high-stakes financial environments.

Slide 7: Differentiation

True multi-agent system: Mirroring the actions of a human associate. · Pre-built app integrations: No manual document uploading required. · Built to handle internal data: Using a specialized knowledge graph. · Precise data orchestration: Honing in on critical document subsets. · Trustworthy, explainable: Including inline citations to sources. · Enterprise-grade security: SOC 2 Type II certified and VPC deployment.

This slide is the most information-dense in the deck, aimed at technical due diligence.

Slide 8: Security & Compliance

Mako doubles down on its security messaging here, claiming to offer the "most secure AI platform for firms." It reiterates the "Your Cloud, Your Data" promise, ensuring that data is never used to train models accessible to others. For private equity firms handling sensitive M&A data, this is a non-negotiable requirement.

Slide 9: Use Cases & Results

The final slide lists eight specific use cases, such as Data Room Analysis, Portfolio Reporting, and Customer Call Synthesis. It includes a key engagement metric: "Mako users typically execute 2-5 tasks per day." While it doesn't name specific clients, the phrase "Top investment firms are already using Mako" signals existing market validation.

What Mako AI Does Well

The deck is exceptionally focused. It doesn't try to be everything to everyone; it speaks the language of a Private Equity Associate. The emphasis on security (Slides 1, 7, and 8) is a masterclass in overcoming sales objections before they are even raised. Furthermore, the team slide (Slide 2) is incredibly strong, providing a 'halo effect' that likely carried significant weight with seed investors.

What is Missing from the Deck

The Ask: There is no slide detailing how much they are raising or what the capital will be used for. · Business Model: The deck does not explain how Mako charges (e.g., per seat, per fund, or consumption-based). · Market Size: There is no TAM/SAM/SOM analysis to show the scale of the opportunity. · Roadmap: The deck focuses entirely on the current product without showing the long-term vision or expansion plans. · Competition: There is no competitive matrix or mention of how they stack up against incumbents like Bloomberg or newer AI rivals.

Lessons for Founders

Founders can learn two major lessons from Mako AI. First, verticalization wins in the AI era. By building specifically for PE, Mako can create workflows (like data room analysis) that a general tool like ChatGPT cannot easily replicate. Second, pedigree is a shortcut to trust. If you have a team with elite institutional experience, lead with it. Mako didn't need 20 slides because their background and their security posture answered the most difficult questions upfront.

Frequently asked questions

How much did Mako AI raise with this deck?: According to publisher-reported facts from Business Insider, Mako AI raised $1.6M in a Seed round in 2024. The deck itself does not state the amount raised or the terms of the round.
What is Mako AI's primary target market?: The deck specifically targets Private Equity, Asset Management, and Professional Services firms. Slide 4 and Slide 9 emphasize workflows unique to these sectors, such as deal sourcing and data room analysis.
How does Mako AI handle data security?: Security is a central theme of the deck. Slide 8 states that Mako is SOC 2 Type II certified and deploys directly into the client's cloud environment (VPC) to ensure data never leaves the firm's control.
Does the deck show any traction or revenue?: The deck does not list revenue or specific customer names. However, Slide 9 claims that 'top investment firms' are using the platform and that users typically execute 2-5 tasks per day.
What makes Mako different from a standard LLM like ChatGPT?: Slide 7 highlights that Mako is a multi-agent system designed for 'messy internal data.' It uses a specialized knowledge graph and provides inline citations to underlying sources to ensure explainability and trust.

Cover slide of the Mako AI pitch deck — Seed 2024 — Mako AI pitch deck, slide 1 (2024)

Mako AI pitch deck: the facts

Company: Mako AI
Year: 2024
Stage: Seed
Slides: 9
Sector: AI, Enterprise, Finance
Deck type: Seed Pitch Deck
Outcome: $1.6M Raised
Headquarters: North America

Mako AI pitch deck PDF

The full Mako AI deck is embedded on this page and can be read slide by slide in the browser — no download or account required. Each slide is covered in the breakdown above.

What the Mako AI pitch deck was used for

This deck is the 9-slide pitch used by Mako AI (later rebranded as Trove AI) to raise approximately $1.55M in a pre-seed/seed round announced in September 2024, led by Khosla Ventures.[2][7] The company positions itself as the "world’s first AI investment associate" that automates complex research, analysis, and drafting workflows for private equity, asset management, and professional services firms.[2][6][7] The deck emphasizes team pedigree from top firms like Bain and enterprise-grade security (including SOC 2 Type II certification), rather than traditional traction metrics, to persuade institutional investors that Mako AI can safely handle sensitive deal data.[2][6] Funds from this round were used to launch the product publicly and scale the AI associate platform for PE and related industries.[2][7]

Business model: AI-powered investment associate software for private equity, asset management, and professional services firms, delivered as an enterprise SaaS platform focused on research, analysis, and drafting workflows.[2][6][7]

Round: Pre-seed/Seed
Year: 2024
Lead investor: Khosla Ventures
Investors: Khosla Ventures

Raised: Approximately $1.55M (reported as $1.5–$1.55M) in a pre-seed/seed round announced September 2024.[1][2][7]

Industry: Financial technology / AI software for private equity and asset management workflows.[2][6][7]

Total funding: At least $1.55M in a pre-seed/seed round led by Khosla Ventures as of September 2024, with later reports of a $7.1M seed round after rebranding to Trove AI (not part of this specific deck).[2][7][10]

Use of funds as presented: Launch and scale Mako as an AI investment associate for private equity, asset management, and professional services, focusing on automating due diligence, research, and drafting workflows with enterprise-grade security.[2][6][7]

What happened after the Mako AI deck

Following the 2024 9-slide deck, Mako AI announced a roughly $1.55M pre-seed/seed round led by Khosla Ventures and launched its AI investment associate product, later rebranding to Trove AI and reportedly securing a larger seed round led by Menlo Ventures.[1][2][7][10]

Public announcement of Mako as the "world’s first AI investment associate" and the $1.55M pre-seed/seed round led by Kho
Subsequent rebranding of Mako to Trove AI, with later reporting of a $7.1M seed round led by Menlo Ventures and continue

What the Mako AI deck got right

Focused positioning on PE and asset management use cases. Clear, niche positioning as the **world’s first AI investment associate** dedicated to private equity and asset management workflows, which helps investors quickly understand the target customer and value proposition.[2][6][7]
Security-first messaging with SOC 2 Type II certification. Strong emphasis on **enterprise-grade security**, including SOC 2 Type II certification and deployment that keeps data within the client’s control and environment, directly addressing a major barrier for AI adoption in PE.[2][6]
High-signal lead investor validation. Backed by **Khosla Ventures** at the pre-seed/seed stage, providing significant external validation of the team and technology and featuring prominently in the fundraising narrative.[1][2][7]
Workflow-centric value proposition for investment teams. Compelling workflow coverage—due diligence acceleration, investment research enhancement, client reporting automation, and institutional knowledge management—mapping directly onto pain points faced by PE and asset management teams.[2][6][7]
Concise deck emphasizing team pedigree and enterprise readiness. The 9-slide deck is concise and focused on team pedigree and enterprise readiness, which can be appealing to institutional investors who prioritize credibility and risk mitigation over detailed early-stage metrics.[2]
Consistent narrative across press, product, and investor materials. Narrative alignment between the Business Insider feature, the company’s announcement blog, and product descriptions reinforces a consistent story around building an AI associate for PE rather than a generic AI tool.[2][6][7]

What could have been stronger

Limited visible traction metrics in the deck. Available reporting indicates the deck and article focus on team pedigree and security but provide no clear evidence of quantitative traction metrics (e.g., user counts, ARR, case studies with quantified ROI), which may leave investors uncertain about early product-market validation.[2]
Differentiation versus other AI workflow tools is not crisply substantiated. The deck frames Mako AI as the "world’s first AI investment associate" and "revolutionary" for PE workflows, but public descriptions rely heavily on broad claims (due diligence acceleration, investment research enhancement) rather than specific, differentiated technical capabilities versus other AI workflow tools.[2][6][7]
Security messaging is strong but lacks publicly visible implementation detail. The deck and associated materials emphasize SOC 2 Type II and secure data handling but do not publicly detail data residency options, on-prem deployments, or granular access controls, which are often critical concerns for PE and asset management firms handling highly sensitive deal information.[2][6]
Go-to-market and customer validation appear under-specified in public view. Publicly available materials do not show clear pricing, deployment models, or customer references tied directly to this 2024 raise, which can make it harder for investors to assess go-to-market strategy and willingness of target PE/asset management customers to adopt the AI associate.[2][6]

How an investor would read this deck

What draws attention

Positioning as the **first AI investment associate** focused specifically on private equity and asset management workflows, which defines a clear niche in AI for finance.[2][6][7]
Strong emphasis on **enterprise-grade security**, including SOC 2 Type II certification and keeping data in clients’ environments, directly addressing PE firms’ sensitivity about confidential data.[2][6]
Backed by **Khosla Ventures** at the pre-seed/seed stage, signaling venture validation of the team and concept.[1][2][7]
Product narrative around automating **due diligence, investment research, and client reporting** for PE and asset management, promising material productivity gains for high-value knowledge work.[2][6][7]

Risks that stand out

Enterprise AI workflow tools for finance are a competitive space, and the deck’s public materials do not clearly demonstrate deep differentiation versus other AI copilots or RAG tools targeting financial services.[2][6][7]
The deck appears to lean more on team pedigree and security than on clearly documented traction, which may indicate that product-market fit was still early at the time of the 2024 raise.[2]
Reliance on sensitive internal documents and data means any security or hallucination issues could significantly damage trust with PE and asset management clients, raising implementation risk despite SOC 2 certification.[2][6]
As the company later rebranded to Trove AI and raised a larger seed round, there is potential for strategic pivots in positioning or product that could partially diverge from the original Mako AI value proposition pitched in this deck.[7][10]

Questions this deck invites

Which specific private equity or asset management firms were live customers or pilots at the time of the 2024 $1.55M round, and what measured productivity or ROI improvements did they see (e.g., time saved per diligence process)?[2][6]
How is Mako AI’s core architecture built (models used, retrieval and orchestration pipeline, guardrails), and what concrete advantages does it have over generic RAG/LLM tools for investment workflows?[2][6][7]
What is the detailed security model (deployment options, data residency, fine-grained permissions, audit logs) underlying the SOC 2 Type II claim, and how does this align with top-tier PE firms’ requirements?[2][6]
What is the pricing and sales motion for selling an AI investment associate into PE and asset management (seat-based, usage-based, or workflow-based), and what early sales cycles looked like for the 2024 raise?[2][6][7]
How does Mako/Trove AI plan to sustain defensibility as general-purpose AI tools improve—through proprietary data, workflows, integrations, or specialized models tuned for PE and asset management use cases?[2][6][7]

What founders can take from the Mako AI deck

A tightly focused narrative like "the world’s first AI investment associate for private equity" can help a seed-stage deck stand out by clearly defining the target user and problem space instead of pitching a generic AI platform.[2][6][7]
Emphasizing enterprise-grade security and certifications such as SOC 2 Type II directly in the deck can be a persuasive element when selling AI products into highly sensitive, data-heavy industries like private equity.[2][6]
Highlighting backing from a well-known firm like Khosla Ventures in the fundraising narrative provides strong social proof that can reduce perceived risk for other investors considering a seed-stage AI company.[1][2][7]
Positioning around concrete workflows (due diligence, investment research, client reporting, knowledge management) rather than abstract AI capabilities makes it easier for investors to understand how the product creates value.[2][6][7]
A short deck (9 slides) that prioritizes team pedigree and security over detailed metrics can still close a meaningful seed round when the market thesis and institutional pain point are compelling.[2]
Clarity about how later branding (e.g., Trove AI) and subsequent rounds relate to the original deck is important for library users to distinguish what was promised at the time of the raise from what evolved afterward.[7][10]

Mako AI pitch deck: common questions

What does Mako AI actually do?

Mako AI is an AI-powered "investment associate" platform designed for private equity, asset management, and professional services firms, automating complex workflows like research, analysis, due diligence, and drafting by securely tapping into a firm’s institutional knowledge.[2][6][7]

How much did Mako AI raise with this pitch deck, and who led the round?

Mako AI raised about $1.55M in a pre-seed/seed round announced in September 2024, with the round led by Khosla Ventures; this 9-slide deck featured in Business Insider was the deck used to secure that financing.[2][1][7]

What is the main pitch of Mako AI’s 9-slide seed deck?

The deck focuses on selling Mako AI as the first AI investment associate for private equity and asset management, highlighting its ability to accelerate due diligence, investment research, client reporting, and knowledge management by analyzing large document sets and internal data securely.[2][6][7]

Which credentials and pedigree does the deck emphasize to investors?

The deck and surrounding materials emphasize that Mako AI is backed by Khosla Ventures and built by a team with experience at top firms such as Bain, using this pedigree to reassure institutional investors about its domain expertise and reliability.[2][6][7]

How does this deck relate to later funding and the Trove AI rebrand?

The deck was used for the September 2024 pre-seed/seed round; subsequent funding, including a reported $7.1M seed round led by Menlo Ventures after the company rebranded to Trove AI, occurred later and is not part of this specific pitch deck’s fundraising story.[2][7][10]