Grasp Pitch Deck: All 11 Slides + Teardown

Grasp Pitch Deck Analysis

Grasp is a Swedish startup that entered the market in 2024 with a clear mission: to replace the 'grunt work' of investment banking and management consulting with an AI-driven assistant. In a sector where junior analysts are famously overworked and billing rates are astronomical, Grasp’s value proposition is rooted in pure economic efficiency. The following teardown examines the 11-slide deck used to secure their $1.9M Seed round.

Slide 1-2: Branding and Positioning

The deck opens with a minimalist aesthetic. Slide 1 and 2 establish the brand name and the core tagline: "The AI Assistant for finance professionals." This is a classic 'high-concept pitch' that avoids technical jargon in favor of a clear role description. By calling it an 'Assistant,' they set expectations for a tool that augments or replaces specific human tasks rather than just providing a new data dashboard.

Slide 3: The Economic Problem

Slide 3 is the strongest slide in the deck. It quantifies the 'inefficiency' of the status quo with a striking figure: "top-tier firms can charge >100 KUSD per week for a team of four junior consultants." It further notes that these consultants, fresh from university, perform work that is "~90% manual and repetitive."

A footnote on this slide breaks down the time allocation: 50% on finding information, 40% on creating output materials, and only 10% on internal meetings and client interactions. This immediately identifies the TAM (Total Addressable Market) not just as a software budget, but as a labor replacement opportunity. The visual icons on the right side of the slide—Find, Sort, Synthesize—map out the exact workflow Grasp intends to automate.

Slide 4-5: The Solution and Product Output

Slide 5 illustrates the 'Grasp' engine. It shows a simple flow: an advisory professional wants to create lists or research markets, they input the request into Grasp, and the output is generated. Crucially, the slide shows screenshots of actual deliverables: "Your list of M&A targets is ready," "Your list of strategic buyers is ready," and "Your market report is ready."

By showing Excel spreadsheets and formatted reports, Grasp proves they understand the 'last mile' of financial consulting. The value isn't just in the data; it's in the delivery format that the senior partner can immediately use in a client presentation.

Slide 6-7: Competitive Landscape and Differentiation

Slide 7 uses a 2x2 matrix to define the competitive landscape. The axes are 'Data Type' (General vs. Domain-specific) and 'AI Sophistication' (No AI vs. Domain-adapted AI). Grasp places itself in the top-right quadrant as the only "End-to-end financial advisory workflow tool."

General-purpose AI: ChatGPT and Perplexity, which lack the specific financial domain training. · Pure data providers: S&P Global, Statista, and Euromonitor, which provide raw data but not the 'work.' · Financial databases with AI search: AlphaSense and Grata, which help find info but don't necessarily build the final PPT/XLSX deliverables. · In-house solutions: Proprietary tools built by McKinsey, BCG, and PwC, which are not available to the broader market of mid-tier and boutique firms.

Slide 8-9: Market Opportunity and Redistribution

Slide 9 presents a sophisticated view of the market. Rather than just showing a growing bar chart, it describes a "massive redistribution of the $1.4 trillion financial advisory market."

The slide compares the 'Historical' market to the 'Future' market. Historically, $1.2-$1.3 trillion is spent on human work. Grasp argues that AI will eat into this human-labor slice. They highlight their addressable market as a significant portion of that trillion-dollar labor spend. This is a bold claim, suggesting that Grasp isn't just a $20/month SaaS tool, but a platform that can capture a portion of the value previously reserved for junior analyst salaries.

Slide 10-11: The Team

The final slide (Slide 11) focuses on credibility. The founding team is a mix of 'insider' knowledge and 'outsider' technical skill. Richard Karlsson (CEO) and Johan Cederqvist (CCO) provide the domain expertise, with backgrounds at McKinsey and various financial institutions (Fidelio Capital, Deutsche Bank, Nordea). Simon Hällqvist (CTO) provides the technical backbone, coming from Ericsson’s AI team.

The slide emphasizes three key points: the founders have worked together for 10+ years , they have deep user experience from top-tier firms, and the tech team has a strong track record of building AI tools with limited resources. This addresses the two biggest risks in a Seed round: 'Can they build it?' and 'Do they understand the customer?'

What Works in the Grasp Deck

The 'Junior Analyst' Anchor: By anchoring the problem to the $100k/week cost of junior consultants, Grasp makes their software feel like a bargain, regardless of the actual price point. · Workflow Focus: They don't just talk about 'AI'; they talk about xlsx and ppt outputs. This shows a deep understanding of how work actually gets done in finance. · Market Redistribution Narrative: Instead of saying the market is growing, they say the market is being disrupted. This is a more compelling narrative for VCs looking for 'category-defining' companies. · Team Pedigree: The combination of McKinsey and Ericsson is a 'perfect' founding pair for a FinTech AI startup.

What is Missing from the Grasp Deck

The Ask: There is no slide detailing how much they are raising or what the milestones are. While we know they raised $1.9M, a pitch deck usually benefits from a clear roadmap of how that capital will be deployed. · Unit Economics: There is no mention of pricing models. Is it per-seat, per-report, or a percentage of labor saved? · Traction: The deck is very conceptual. There are no mentions of pilot programs, early design partners, or waitlist numbers. For a 2024 Seed round, investors usually look for at least some evidence of 'proof of concept' with a real firm. · Data Sources: While they mention 'trusted sources,' they don't specify if they have proprietary data partnerships or if they are scraping public filings and web data. In finance, data provenance is a major compliance hurdle.

Founder's Guide: What to Copy

The 2x2 Matrix Strategy: Use Slide 7 as a template. Don't just list competitors; group them by 'what they lack' (e.g., 'No AI' or 'General Data') to make your position in the top-right quadrant feel inevitable. · Quantify the Inefficiency: If you are building B2B software, find the 'human cost' of the problem you are solving. Grasp's use of the '$100k per week' figure is a brilliant way to frame the ROI. · Show the Output: Don't just show the UI of your app. Show the final file the user sends to their boss. That is the actual 'value' the customer is buying. · Highlight Team Longevity: If you have worked with your co-founders for a long time, state it explicitly. 'Worked together for 10+ years' is a massive de-risking signal for investors who fear founder conflict.