Depict.ai Pitch Deck: All 10 Slides + Teardown

See all 10 slides of the Depict.ai pitch deck — a 2020 Seed deck — with a slide-by-slide teardown of what the deck does well and where it falls short.

Depict.ai’s 2020 Seed deck is a high-signal, low-noise presentation that successfully raised $2.9M by focusing on proof of value. Rather than getting bogged down in the mechanics of their AI, the founders leveraged a 'Unique Insight' slide to explain why traditional recommender systems fail and how their computer vision approach yields 2-6x better results. The deck is heavily weighted toward social proof, featuring a dedicated slide for a Staples contract and a logo wall of over 20 customers. Most notably, the business model is built on a 10% cut of revenue uplift, transforming the product fr…

Key takeaways

Executive Summary: High-Signal Simplicity

Depict.ai’s Seed deck is a study in brevity. Raised in 2020, this $2.9M round was secured using just 10 slides that largely ignore the 'how' of the technology to focus entirely on the 'what' of the results. In an industry—AI for e-commerce—crowded with buzzwords, Depict.ai chose to lead with logos and A/B test data. By the time an investor reaches the end of the deck, the technical feasibility is assumed because the commercial results are already on the page.

Slide 1: Title and Value Proposition

The deck opens with a minimalist title slide. The sub-headline, "Amazon-quality product recommendations for any e-commerce store," is a classic 'X for Y' positioning statement. It identifies the gold standard (Amazon) and the target market (any e-commerce store) immediately. There are no decorative graphics, just a clear promise of value.

Slide 2: The Team

The team slide is strategically placed early to establish technical authority. CEO Oliver Edholm is highlighted as being "Just turned 18 y/o" and the "Youngest AI-researcher in the world," with experience at Klarna. Anton Osika is positioned as the technical anchor with "ex-CERN" credentials and experience as the first employee at Sana Labs. By lead-loading the deck with these credentials, the founders preemptively answer questions about their ability to build complex neural networks.

Slide 3: The Anchor Tenant

Slide 3 is an unusual but effective choice: a single-customer spotlight. It announces a "Signed deal with Staples." The text notes that Staples is expected to expand the contract to the "whole of Europe in 2-3 months." Using a household name like Staples so early in the deck serves as a massive de-risking mechanism for investors, proving that the product can scale to enterprise-level requirements.

Slide 4: The Logo Wall

Following the Staples spotlight, Slide 4 displays a broader customer base. It features 11 logos including RoyalDesign, Nudie Jeans co, KitchenTime, and LloydsApotek , with a footer stating "+10 others." This indicates that the company had at least 21 customers at the time of the Seed round, a significant amount of traction for a startup at this stage.

Slide 5: The Unique Insight

This is the 'Problem/Solution' hybrid slide. Depict.ai argues that "All existing recommender systems solely rely on transaction data." Their insight is that by understanding "images and text like a human does," they can perform "2-6x better." The visual shows a fashion model with a bounding box, suggesting computer vision is the core differentiator. This slide explains the 'secret sauce' without needing a deep dive into architecture.

Slide 6: The Data Scarcity Problem

Slide 6 reinforces the 'Unique Insight' by explaining the market pain point. It states that "Individual e-commerce stores do not ever have enough data" to do recommendations properly. It draws a parallel to credit card fraud detection, noting that a single store lacks the aggregate data to predict outcomes. This sets the stage for why a third-party AI layer like Depict.ai is a necessity rather than a luxury.

Slide 7: The Business Model

The 'How we sell' slide is perhaps the strongest in the deck. It outlines a low-friction sales funnel: 1. Show comparisons, 2. Offer a free 2-week A/B test, and 3. "Take a 10% cut of the overall revenue uptick." This performance-based pricing is a 'no-brainer' for customers, as they only pay if the software makes them money. For investors, this signals a highly scalable, high-margin recurring revenue stream tied directly to customer success.

Slide 8: A/B Test Results

Slide 8 provides the empirical proof for the claims made on Slide 5. It compares Depict.ai against three benchmarks:

Amazon Web Services: 2x increase in click-through rate vs AWS Personalize. · Largest competitor (Nosto): 150% increase in add-to-cart for the customer Reforma. · In-house data scientist: 270% increase in revenue from recommendations for KitchenTime.

This slide effectively kills the 'competition' objection by showing head-to-head wins against both giants (AWS) and incumbents (Nosto).

Slide 9: Market Size (TAM)

The market slide uses a simple bottom-up calculation. It takes a "$3T E-commerce market," applies a "4% average overall revenue uplift," and then applies their "10% Cut on revenue increase" to arrive at a "$12B TAM." This is a logical, defensible way to show how a niche tool can become a multi-billion dollar opportunity.

Slide 10: Conclusion

The deck ends abruptly with a "Thank you" slide. There is no contact information, no 'Ask,' and no roadmap. While this works for a deck intended to be presented live, it leaves a gap for a deck sent as a standalone file.

What Depict.ai Does Well

The primary strength of this deck is its focus on outcomes over features . Many AI startups spend five slides explaining their transformer models or data pipelines; Depict.ai spends one slide on the 'insight' and three slides on the revenue they generate for customers. The inclusion of the Staples contract expansion (Slide 3) and the specific A/B test percentages (Slide 8) creates a sense of inevitability. Furthermore, the business model (Slide 7) is perfectly aligned with the customer's incentives, which is a powerful narrative for a Seed-stage company trying to prove product-market fit.

What is Missing from the Deck

The most glaring omission is the Funding Ask . There is no mention of how much the company is raising ($2.9M, as reported by Business Insider) or what the milestones for the next 18 months look like. Additionally, there is no Product Roadmap . Investors are left wondering if Depict.ai intends to stay purely in recommendations or expand into search, personalization, or inventory management. Finally, while the team slide is impressive, it lacks a Sales/GTM lead , which is a common concern for technical-heavy founding teams in the e-commerce space.

Founder's Playbook: What to Copy

Founders should emulate the Performance-Based Pricing slide (Slide 7) . If your software has a measurable impact on a customer's bottom line, stating that you take a percentage of that 'uplift' is the most compelling way to demonstrate value. Also, the Competitive Benchmarking (Slide 8) is a masterclass in positioning. By naming AWS and Nosto, Depict.ai isn't just saying they are 'good'; they are saying they are 'better than the best.' If you have A/B test data against a known incumbent, it should be the centerpiece of your deck. Lastly, the Unique Insight (Slide 5) is a great way to simplify complex tech. Instead of explaining the math, explain why the current way of doing things is fundamentally broken and how your 'insight' fixes it.

Frequently asked questions

How does Depict.ai differentiate itself from other AI recommendation engines?
According to Slide 5, most systems rely solely on historical transaction data. Depict.ai claims a 'Unique Insight' by using algorithms that understand product images and text 'like a human does.' This allows them to provide relevant recommendations even without a massive history of user purchases, which they claim leads to a 2-6x performance improvement over traditional methods.
What is the specific business model presented in the deck?
Slide 7 outlines a three-step sales process: showing a demo comparison, offering a free 2-week A/B test to prove revenue impact, and then charging a monthly recurring fee equal to a 10% cut of the overall revenue uptick. This performance-based approach reduces the barrier to entry for skeptical e-commerce managers.
Who are the competitors mentioned in the Depict.ai deck?
Slide 8 explicitly names three competitive benchmarks: Amazon Web Services (specifically AWS Personalize), Nosto (referred to as the 'Largest competitor'), and 'In-house data scientists.' The slide uses A/B test data from customers like Reforma and KitchenTime to show superior performance against these alternatives.
What is the background of the founding team?
Slide 2 highlights CEO Oliver Edholm as an 18-year-old former AI researcher at Klarna and the 'youngest AI-researcher in the world.' Co-founder Anton Osika is described as an ex-CERN researcher and the first employee at Sana Labs. The slide uses logos from Klarna, NUS, and CERN to anchor their technical credibility.
Is there a clear financial 'Ask' in this pitch deck?
No. The 10-slide deck concludes with a 'Market' slide and a 'Thank you' slide. It does not state how much money the company is looking to raise, the valuation, or how the funds will be spent. This information was likely reserved for the verbal pitch or a supplemental data room.
Cover slide of the Depict.ai pitch deck — Seed 2020
Depict.ai pitch deck, slide 1 (2020)

Depict.ai pitch deck: the facts

Company
Depict.ai
Year
2020
Stage
Seed
Slides
10
Sector
AI, E-commerce
Deck type
Seed Pitch Deck
Outcome
$2.9M Raised
Headquarters
Europe

Depict.ai pitch deck PDF

The full Depict.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 Depict.ai pitch deck was used for

This is Depict.ai’s 2020 seed pitch deck for an AI product-recommendation and merchandising tool for e-commerce stores. The deck was used around the company’s seed fundraising in 2020, when the company said it could deliver Amazon-like recommendations without relying on historical transaction data. The deck leaned on a small set of slides, customer proof, and performance claims rather than technical depth.

Business model: B2B SaaS AI product recommendations and merchandising for e-commerce stores

Round
Seed
Year
2020
Raised
$2.7M-$2.8M
Lead investor
Initialized Capital
Investors
Initialized Capital, Y Combinator, EQT Ventures, Liquid 2 Ventures, Northzone
Founded
2019
Founders
Anton Osika, Oliver Edholm
Headquarters
Stockholm, Sweden
Industry
AI e-commerce / product discovery
Total funding
$19.9M

What happened after the Depict.ai deck

The company’s seed deck appears to have helped it secure a 2020 round, and later reporting shows it continued to raise capital and scale beyond the initial fundraise.

What the Depict.ai deck got right

What could have been stronger

How an investor would read this deck

What draws attention

Risks that stand out

Questions this deck invites

What founders can take from the Depict.ai deck

Depict.ai pitch deck: common questions

How much did Depict.ai raise in the seed round?

Depict.ai raised a seed round in 2020; the sources I found report either $2.7M or $2.8M, so the exact amount is not fully consistent across references.

Who invested in Depict.ai’s seed round?

The seed round was led by Initialized Capital, with participation reported from Y Combinator, EQT Ventures, Liquid 2 Ventures, and Northzone.

Who founded Depict.ai and where is it based?

The company was founded in 2019 and was based in Stockholm, Sweden, according to company and YC profiles.

What was Depict.ai’s main pitch in the deck?

The deck’s core claim was that its recommendations beat existing recommender systems by 2–6x because it used product images and text, not just transaction data.

What happened to Depict.ai after this deck?

Later reporting said Depict.ai raised a $17M Series A in 2022 led by Tiger Global, showing the company progressed beyond the seed stage.

Sources

Funding and outcome facts on this page were researched on 2026-08-30 from the pages below.

Depict.ai pitch deck slides

Depict.ai pitch deck slide 1 of 10
Depict.ai pitch deck — slide 1 of 10
Depict.ai pitch deck slide 2 of 10
Depict.ai pitch deck — slide 2 of 10
Depict.ai pitch deck slide 3 of 10
Depict.ai pitch deck — slide 3 of 10
Depict.ai pitch deck slide 4 of 10
Depict.ai pitch deck — slide 4 of 10
Depict.ai pitch deck slide 5 of 10
Depict.ai pitch deck — slide 5 of 10
Depict.ai pitch deck slide 6 of 10
Depict.ai pitch deck — slide 6 of 10

What each slide of the Depict.ai pitch deck says

Slide 1

- - Depict.ai Amazon-quality product recommendations for any e-commerce store

Slide 2

Oliver Edholm, CEO Anton Osika Youngest Al-researcher in the world First employee at Sana Labs (now 30+ ex-Klarna (Al research) employees] Just turned 18 y/o ex-CERN Klarna. $% Sana Labs SANUS CC)BABYSHOP BS GROUP

Slide 3

Si 9 ned deal Staples is one of our customers. We expect to Sta P es expand our contract to the whole of Europe in 2-3 months when they're launching their “Intershop”-platform

Slide 4

Customers KITCHENTIME MEDS J. RoyalDesign = Wudie JeAns co LloydsApotek — o JUNKYARD. FPELAD GRAN mini rodini DPA STAPLES Dogman +10 others 4

Slide 5

Unique Insight All existing recommender systems solely rely on transaction data to recommend products. Our recommendations perform 2-6x better because we know far more about any product other than just the transactions. This is enabled by our algorithms understanding images and text like a human does.

Slide 6

Individual e-commerce stores have enough data felel=¥:lell=RreXele} recommendations in the right way, just like with any single e-commerce store to detect which credit card will be fraudulent, they will not have enough data {elet=le[{e1RWallely] products will sell.

Slide text above is read directly from the Depict.ai deck PDF embedded on this page.

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