Deep Render Pitch Deck: All 50 Slides + Teardown

Deep Render’s 50-slide deck is a highly technical presentation that successfully raised $9M in 2022. The company addresses the massive infrastructure costs of global data transmission by proposing a complete rebuild of video compression using AI. The deck relies heavily on Mean Opinion Score (MOS) data to prove their technology outperforms industry standards like AV1 and HEVC by significant margins—specifically claiming up to 81.52% better performance than AVC. By targeting high-bandwidth markets like India and outlining a dual-revenue stream through encoder and decoder licensing, Deep Render…

Key takeaways

• Deep Render claims their technology outperforms the AVC standard by 81.52% in video compression efficiency (Slide 4).
• The company identifies a massive infrastructure problem, noting that extending submarine fiber optic networks costs trillions of dollars (Slide 2).
• The business model is split into two distinct markets: Enterprise License Agreements for Encoders and usage-based royalties for Decoders (Slide 7).
• Deep Render targets the Indian market specifically, where 100M VoD users are currently limited by a 2-3GB daily data cap (Slide 6).
• The technology is designed to work across diverse hardware, including Apple NPUs, Qualcomm NPUs, and NVIDIA Tensor Cores (Slide 9).
• The deck positions the product as a necessity for high-growth sectors like VR/AR streaming and cloud gaming (Slide 5).
• A six-stage sales pipeline is presented, moving from outreach to a final rollout, with reference calls explicitly offered to investors (Slide 8).
• Performance metrics show Deep Render achieving a MOS of 4.5 at significantly lower bitrates (approx. 1.5 Mbps) compared to competitors (Slide 4).

Frequently asked questions

What is the primary problem Deep Render is solving?

Deep Render addresses the 'trillion-dollar' problem of global bandwidth limitations. As stated on Slide 2, physical infrastructure like submarine cables is prohibitively expensive to expand. By rebuilding compression with AI, they allow existing infrastructure to carry more high-quality data, effectively 'unlocking' markets where users are currently restricted by low data caps and slow speeds.

How does Deep Render's performance compare to existing video standards?

According to the performance chart on Slide 4, Deep Render significantly outperforms current standards. It shows a -66.56% improvement over AV1, -73.68% over HEVC, and -81.52% over AVC. This means they can deliver higher visual quality (measured by Mean Opinion Score) at a fraction of the bitrate required by traditional codecs.

What is the company's go-to-market strategy for India?

Slide 6 highlights India as a key growth market with 100 million Video-on-Demand (VoD) users. Because these users face a 2-3GB daily data cap, they are often limited to Standard Definition (SD) content. Deep Render claims their tech enables an effective cap of 10-15GB/day, allowing HD content for the masses and giving providers a competitive edge.

How does Deep Render plan to make money?

The company utilizes a two-pronged licensing model detailed on Slide 7. For the 'Encoder Market,' they offer Enterprise License Agreements with fixed pricing and one-year terms. For the 'Decoder Market,' they use End-User License Agreements with fixed price-per-usage or IP royalties, billed annually based on activated accounts.

What hardware is required to run Deep Render's AI compression?

Slide 9 shows that the technology is hardware-agnostic but optimized for AI-specific processors. For encoding, it utilizes GPUs and Tensor Cores. For decoding, it supports a wide range of Neural Processing Units (NPUs) from manufacturers like Apple, Qualcomm, Samsung, and MediaTek, as well as standard CPUs.

Deep Render pitch deck: the facts

Company

Deep Render

Year

2022

Stage

Series A

Slides

50

Sector

AI / Video Compression

Deck type

Technical / Fundraising Deck

Outcome

$9M Raised

Headquarters

Europe (London, UK)

Deep Render pitch deck PDF

The full Deep Render 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 Deep Render pitch deck was used for

This deck is Deep Render’s Series A fundraising pitch used around early 2023 to raise a $6.3M equity round plus a $2.7M European Innovation Council grant, totaling $9M.[2][3][4][13][14] Deep Render is a London-based deep tech startup developing next-generation AI-first video and image compression technology to address global bandwidth constraints.[1][4][8][11] The deck focuses heavily on the societal-scale bandwidth problem, customer willingness to pay, and an imminent need for better compression, positioning Deep Render’s codec as a fundamental technology shift using an AI-first approach, with a dual-licensing/commercial model highlighted in coverage.[2][4] Although the raise closed in 2023, Business Insider and other sources describe this funding as a Series A round for which this deck was used, following earlier seed financing in 2020 and subsequent funding.[2][10][11][6]

Business model: Deep Render develops an AI-first image and video compression codec that runs as software on servers for transcoding/encoding and on end-user devices for decoding, sold as compression software to content owners and platforms to reduce bandwidth and storage costs.[5][8]

Round

Series A[1][2][3][4][13][14]

Lead investor

IP Group and Pentech Ventures co-led the Series A equity round.[1][2][3][4][13][14]

Investors

IP Group, Pentech Ventures, European Innovation Council[1][2][3][4][13][14]

Founded

2018[4][8][11]

Founders

Chri Besenbruch, Arsalan Zafar[4][11]

Headquarters

London, England, United Kingdom[1][4][8][11]

Industry

AI-based image and video compression / deep tech[1][4][8][11]

Year: 2023 (Series A round completed around February–March 2023, although some coverage frames it as a 2022-raised deck).[1][2][3][12][13][14]

Raising: Series A funding to further develop and commercialize its AI-powered video compression technology, including product R&D, parallelizing commercial engagements, shifting customer acquisition efforts toward the U.S., doubling the team, and supporting patent plans.[1][2][3][4][14]

Raised: $6.3M equity plus $2.7M grant, totaling $9M.[2][3][4][13][14]

Total funding: Approximately $15M total funding as of the 2023 Series A plus prior rounds.[4][10][14]

Use of funds as presented: Product R&D, accelerating and parallelizing commercial engagements, shifting focus to U.S. customer acquisition, doubling the team, and fueling patent and IP strategy.[1][4][14]

What happened after the Deep Render deck

After using this deck to raise a $9M Series A round combining equity and a European Innovation Council grant, Deep Render continued to develop and commercialize its AI-first video and image compression codec, expanding its team and commercial efforts, and was eventually acquired by InterDigital in 2025.[1][2][3][4][7][10][11][14][15]

• Deep Render raised a $6.3M Series A equity round led by IP Group and Pentech Ventures, complemented by a $2.7M European
• Prior to the Series A, Deep Render closed a £1.6M seed round led by Pentech with participation from Speedinvest in 2020
• Following the Series A, media coverage reports the company planned to double its team, accelerate commercial engagement,
• In October 2025, InterDigital announced that it had acquired Deep Render, citing its pioneering AI-based video and image

What the Deep Render deck got right

• Compelling framing of a systemic bandwidth and data crisis. The deck highlights a "problem of massive scale for society" and impending bandwidth collapse, aligning closely with widely reported exponential growth in video traffic and internet data consumption, which frames a very large and urgent market opportunity for improved compression.[2][3][4][10][11]
• Powerful customer validation of pain and savings potential. Quotes from enterprises stating that better compression would save "hundreds of millions" and that "all know that the pipes are broken; bandwidth is the dominating cost" directly validate customer pain and willingness to pay, providing strong qualitative demand evidence in the deck.[2]
• Clear AI-first technological differentiation and performance claims. Deep Render positions its solution as a "massively better" compression algorithm/codec made possible by a fundamental shift to an AI-first approach, which external coverage reinforces by describing up to 80% smaller file sizes and 5x effective bandwidth increases, giving the deck a clear technological differentiation narrative.[1][4][8][11]
• Strong emphasis on technical metrics and a defined commercial model. Business Insider notes that the deck stands out for its heavy focus on technical performance metrics and a clear dual-licensing business model, suggesting that the slides combine deep technical detail with a concrete commercialization framework that investors can evaluate.[2]
• Value proposition of avoiding costly infrastructure upgrades. The deck explicitly connects improved compression to avoiding major infrastructure overhauls, emphasizing that Deep Render’s software-only codec can increase bandwidth capacity using existing networks, which is attractive for customers seeking cost-effective solutions.[2][4][8]
• Demonstrated investor and strategic validation of the deck’s thesis. The subsequent successful $9M Series A round and later acquisition by InterDigital indicate that the narrative and technology presented in the deck resonated with both financial and strategic investors, validating its core thesis and positioning.[1][2][3][4][7][13][14][15]

What could have been stronger

• Limited explicit traction and revenue detail in visible slides. The OCR snippets and Business Insider description indicate the deck strongly emphasizes the abstract, macro-level "deep tech opportunity" and societal bandwidth collapse, but there is limited visible detail on specific customer traction metrics, current deployments, or revenue figures within the slides we see; this may leave investors with questions on near-term commercial validation beyond anecdotal quotes.[2]
• Lack of standardized benchmark evidence in the deck excerpts. The deck text and external coverage focus on technical performance (claims of up to ~80% compression improvement and 5x bandwidth capacity), but publicly available materials do not show clear, independently validated benchmarks against standard codecs (e.g., H.264, AV1) or standardized test suites within the deck, which could raise diligence questions about reproducibility and real-world performance across varied content types.[1][4][8][11]
• Go-to-market and pipeline details only partially articulated. While the deck references "customers + willingness to pay" and includes quotes suggesting that better compression would save "hundreds of millions," the available excerpts do not specify the pipeline composition, deal stages, or pricing/contract structures, potentially making the commercial model and go-to-market less concrete to investors at this stage.[2]
• Integration and standards compatibility not fully detailed in the deck. External sources state that Deep Render’s technology runs on devices and servers, but there is no clear evidence from the deck excerpts about how the codec integrates into existing workflows, licensing terms, or standards compatibility, which can be critical for adoption by large media and platform customers.[4][5][8]

How an investor would read this deck

What draws attention

• The deck’s framing of a "problem of massive scale for society" and an impending bandwidth "collapse" maps directly to the widely recognized growth of video traffic and data consumption, which investors view as a large, structural market opportunity.[2][3][4][10][11]
• Quotes from prospective or current customers about broken bandwidth "pipes" and compression savings of "hundreds of millions" demonstrate strong willingness to pay and validate that bandwidth is a dominant cost driver for large video platforms, which is compelling for investors evaluating market dem
• The AI-first codec positioning, described externally as delivering up to 80% smaller file sizes or 5x effective bandwidth capacity, provides a clear technological differentiation and potential moat in a space dominated by incremental improvements to traditional codecs.[4][8][11]
• Coverage notes a clear use of funds toward product R&D, parallelizing commercial engagements, shifting customer acquisition efforts toward the U.S., doubling the team, and fueling patent plans, which aligns with investors’ focus on scaling both technology and market presence post-Series A.[1][4]
• The later acquisition of Deep Render by InterDigital in 2025 demonstrates that the company’s technology and team were strategically valuable to a larger industry player, retroactively validating the core thesis of the Series A deck from an investor exit perspective.[7][15]

Risks that stand out

• Compression performance claims (e.g., up to 80% improvement or 5x effective bandwidth) may not generalize across all content types or real-world network conditions, and without broad third-party validation, investors risk overestimating the technology’s impact.[1][4][8][11]
• The market for video compression is competitive and dominated by established standards and large companies; convincing infrastructure providers and platforms to adopt an AI-first codec may involve long sales cycles, integration challenges, and standards convergence risk.[1][4][10][11]
• Heavy reliance on a deep tech, AI-heavy R&D roadmap means execution risk if the company cannot maintain a technical lead or if compute costs and hardware constraints limit the practicality of deployment at internet scale.[1][4][8][10]
• Regulatory and ecosystem dynamics in video delivery (e.g., device compatibility, streaming platform policies) could affect adoption, particularly if the codec does not align with emerging open standards or if proprietary integration is required.[4][8][11]
• Although Deep Render ultimately achieved an acquisition by InterDigital, there is always inherent risk at the Series A stage that strategic or financial exit opportunities may not materialize if technology fails to reach widespread commercial adoption.[7][15]

Questions this deck invites

• What are Deep Render’s independently validated compression performance metrics versus existing codecs (e.g., H.264, HEVC, AV1) across different content types, and which third-party or customer benchmarks can be shared beyond the internal re
• Which specific customers or pilot partners were generating paid revenue or signed commercial agreements at the time of the Series A deck, and what were the average deal sizes, contract durations, and pricing models?[2][4]
• How does Deep Render’s codec integrate with existing media and streaming workflows (e.g., cloud encoding pipelines, CDNs, device decoders), and what are the key technical or standards-related barriers to adoption?[4][5][8]
• What is the company’s IP position, including granted patents and pending applications, and how defensible is its "AI-first" compression approach against incumbents and other AI-based compression startups?[4][8][11]
• What were the projected unit economics and scalability assumptions in the Series A plan (e.g., compute costs, licensing fees, margin profile), and how did those assumptions compare to actual performance and costs observed in early deploymen

What founders can take from the Deep Render deck

• Framing the bandwidth and data crisis as a "problem of massive scale for society" can effectively communicate that a deep tech solution addresses a systemic, not merely incremental, issue, which helps investors anchor the opportunity in macro trends.[2][3][4][10][11]
• Including direct customer quotes about broken bandwidth "pipes" and savings of "hundreds of millions" provides powerful qualitative evidence of pain and willingness to pay, which can be more persuasive than abstract market sizing alone.[2]
• Positioning an AI-first codec as a fundamental technological shift, rather than just an optimization tweak, can differentiate a startup in a mature, standards-driven market and justify deep tech R&D investment.[1][4][8][11]
• Combining equity and a competitive grant (such as the European Innovation Council’s $2.7M grant) in a single round can increase total capital without additional dilution, showing how non-dilutive funding can be integrated into a pitch narrative.[2][3][4][13][14]
• Clearly articulating use of funds—such as focusing on product R&D, parallelizing commercial engagements, shifting to the U.S. market, team growth, and patent expansion—helps investors see a credible path from technology development to scaled commercialization.[1][4]
• A deep tech Series A focused on core technology and strategic positioning can still lead to a later acquisition by a larger industry player, illustrating that strong technical differentiation and a focused market narrative can be attractive for strategic exits.[7][15]

Deep Render pitch deck: common questions

What does Deep Render do?

Deep Render is a London-based deep tech startup that develops AI-first image and video compression technology, offering a codec that can shrink video sizes significantly (up to around 5x or 80% smaller files as described in company materials) without compromising streaming quality.[4][8][11] Its technology is designed to run on servers for transcoding and on end-user devices for decoding, targeting content owners and platforms facing high bandwidth and storage costs.[5][8]

How much did Deep Render raise in its Series A and who invested?

Deep Render raised a total of $9M in its Series A funding round: $6.3M in equity led by IP Group and Pentech Ventures, and a $2.7M grant from the European Innovation Council.[2][3][4][13][14] Various reports note this round closed around February–March 2023, with sources describing it as a Series A raise for its AI-powered video compression technology.[1][2][3][4][12][13][14]

Who led Deep Render’s Series A round?

According to TechCrunch and other sources, the $6.3M Series A equity round was led by IP Group and Pentech Ventures, with additional support from a competitive $2.7M grant from the European Innovation Council; the combination brought the total round size to $9M.[1][2][3][4][13][14] Earlier funding included a £1.6M seed round in 2020 led by Pentech with participation from Speedinvest.[10][11]

Was this specific pitch deck used for Deep Render’s Series A fundraising?

Business Insider and other coverage indicate that Deep Render used this pitch deck to secure its $9M Series A round, comprising a $6.3M equity raise and a $2.7M European Innovation Council grant.[2][3][4][13][14] The deck emphasizes the massive societal-scale bandwidth problem, customer quotes about broken bandwidth "pipes" and high costs, and Deep Render’s AI-first codec as a solution, consistent with the company’s public positioning in articles and on LinkedIn.[1][2][4][5][8][11]

What happened to Deep Render after its Series A round?

Subsequent to the Series A, InterDigital announced in October 2025 that it acquired Deep Render, describing it as an AI startup focused on video codecs and highlighting its pioneering use of AI in video and image compression.[7][15] This acquisition represents a later-stage outcome that occurred after the time of the Series A deck and fundraising.[7][15]

Sources

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

• Deep Render lands $9M for its AI-powered video compression tech
• Deep Render: AI Startup Secures $9 Million With This Pitch Deck
• Startup combatting the internet's 'ticking time bomb' scoops £7.3m
• This London startup bags $9M for AI-based video compression tech
• Arsalan Zafar | LinkedIn
• Deep Render company information, funding & investors
• InterDigital acquires AI startup Deep Render
• Deep Render | LinkedIn

Deep Render pitch deck slides

What each slide of the Deep Render pitch deck says

Slide 2

DEEP RENDER THE DEEP TECH OPPORTUNITY 1. Problem of massive scale for society 2. Customers + Willingness to pay DEEP RENDER DECK

Slide 3

DEEP RENDER THE PROELER - RS B G 2 Exponential growth World's bandwidth Leading to: collapse Big Tech does of internet data capacity is limited of the internet not like this DEEP RENDER DECK

Slide 4

DEEP RENDER THE PROBLEM: EXPONENTIAL = GROWTH OF DATA ON THE INTERNET o 1% Amount of data on the Internet doubles GLOBAL TRAFFIC, EXABYTES/MONTH every 2-3 years. Media accounts for more than 85% of all data. - oi = 600 . 500 = 400 350 _— - 1 : 20s 200 150 ? I -_— ie US invests $808 every yea om 2a 208 2 — ae $100B in Government subsidies DEEP RENDER DECK

Slide 5

DEEP RENDER THE PROBLEM: CURRENT = COMPRESSION TECHNOLGIES lo ARE RUNNIMG OUT OF STEAR p= % AVERAGE RELATIVE FILE SIZE, % ne sole hy 920 Co’ Ca . 2 0 - 4 56 The Intemet in the US will face Te pes oie pert severe bottlenecks by 2024 DEEP RENDER DECK

Slide 6

DEEP RENDER An example: just extending the Earth's | H EF So ALE J F Submarine Fibre Optic Cable Network would cost trillions of dollars DEEP RENDER DECK

Slide 7

DEEP REMDER Do Companies face this problem? "[...] better compression would save us hundreds of millions" Redacted "[...] all know that the pipes are broken; bandwidth is the dominating cost" Redacted DEEP RENDER DECK

Slide 11

DEEP RENDER THE DEEP TECH OPPORTUNITY 1. Problem of massive scale for society 2. Customers + Willingness to pay DEEP RENDER DECK

Slide 12

DEEP RENDER SOLUTICON m Imminent need for improved compression to increase world's bandwidth capacity without major infrastructure overhaul m Deep Render is developing a massively better compression algorithm/codec Possible due to a fundamental compression technology shift: using an Al-first approach DEEP RENDER DECK

Slide text above is read directly from the Deep Render deck PDF embedded on this page.

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