learn
intermediate
Claude
ChatGPT
Gemini
Gamma
How to Use AI to Prepare Investor Decks and Pitch Materials
A practical workflow for using AI to build pitch narratives, structure decks, and adapt materials for different investor audiences.
9 min read21 February 2026
fundraising
pitch deck
investor presentation
startup
AI writing
What this covers: A step-by-step workflow for using AI to build the narrative, structure, and content of your investor pitch, not just the slides
Who it's for: Founders, startup operators, and fundraising leads preparing Series A through C materials
What you'll walk away with: A tested process for drafting your pitch story, stress-testing claims, adapting for different investor profiles, and generating slide content that doesn't read like a template
Asia angle: Specific guidance on adjusting pitch narratives for Southeast Asian VCs, Japanese corporates, and global investors entering APAC
Why This Matters
Most founders spend weeks on their pitch deck. They agonise over slide design, font choices, and whether the gradient on slide 7 looks right. Then they walk into a meeting and get taken apart because slide 3 makes a market sizing claim they can't defend, and the business model slide reads like it was copied from a YC demo day template. Which it was.
The actual hard work of a pitch isn't the slides. It's the narrative structure, the logic chain from problem to solution to traction to ask, and the ability to tell a slightly different version of that story depending on who's sitting across the table. A Singapore-based VC who's seen 400 SEA fintech pitches this year needs a different emphasis than a Japanese corporate VC evaluating their first regional investment. A global fund looking at Southeast Asia wants to hear about regulatory moats and market fragmentation in ways that a local angel investor already understands intuitively.
AI is genuinely useful here, but not for the reason most people think. It's not about generating pretty slides (Gamma and Beautiful.ai handle that). It's about using AI as a thinking partner to pressure-test your narrative, identify gaps in your logic, and rapidly adapt your pitch for different audiences. That's what this guide covers.
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The actual hard work of a pitch isn't the slides. It's the narrative structure, the logic chain from problem to solution to traction to ask, and the ability to tell a slightly different version of that story depending on who's sitting across the table. A Singapore-based VC who's seen 400 SEA fintech pitches this year needs a different emphasis than a Japanese corporate VC evaluating their first regional investment. A global fund looking at Southeast Asia wants to hear about regulatory moats and market fragmentation in ways that a local angel investor already understands intuitively.
AI is genuinely useful here, but not for the reason most people think. It's not about generating pretty slides (Gamma and Beautiful.ai handle that). It's about using AI as a thinking partner to pressure-test your narrative, identify gaps in your logic, and rapidly adapt your pitch for different audiences. That's what this guide covers.
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How to Do It
1
### Step 1: Dump everything into a narrative brief
Before you touch any slide tool, open Claude or ChatGPT and give it everything you have. Your one-pager, your internal metrics doc, your previous deck, your product description, your competitive notes. Paste it all in. Then ask for a structured summary of your company's story in the format: Problem, Solution, Why Now, Market, Traction, Business Model, Team, Ask.
This isn't about getting AI to write your pitch. It's about seeing your own story reflected back with fresh structure. You'll immediately notice which sections are thin. If the AI can't produce a compelling "Why Now" from everything you gave it, that's because you don't have one yet.
### Step 2: Build the logic chain before the slide order
Most pitch templates give you a slide order. Slide 1: Title. Slide 2: Problem. Slide 3: Solution. That's fine for structure, but it skips the harder question of whether your argument actually holds together.
Ask AI to evaluate your pitch as a sequence of claims. Each slide makes an implicit promise to the investor, and the next slide should deliver on it. If your problem slide describes a $40 billion market but your traction slide shows $12K in monthly revenue, there's a gap. AI is good at finding these gaps when you prompt it correctly.
### Step 3: Draft the slide content as spoken narrative first
Write each slide's content as what you would actually say when presenting it, not as bullet points. Give AI the context for each slide and ask it to draft 3-4 sentences you'd speak aloud while that slide is up. Then condense those sentences into 2-3 bullet points for the actual slide.
This approach produces much better slide copy than asking AI to "write bullet points for a problem slide." Spoken narrative has natural emphasis and flow. Bullet points written in isolation tend to be generic.
### Step 4: Stress-test every claim
This is where AI pays for itself. Take every quantitative claim in your deck and ask AI to challenge it. "We're targeting a $15 billion TAM in Southeast Asian digital payments." Is that credible? Where does that number come from? How do investors in this space typically react to that sizing? What would a sceptical Series A investor push back on?
You want AI to play the role of a well-informed but slightly hostile investor. Claude is particularly good at this if you set the right system context. ChatGPT tends to be more encouraging, which isn't what you need here.
### Step 5: Create investor-specific variations
This is the step most founders skip, and it matters enormously in Asia. A pitch to East Ventures in Jakarta should emphasise different things than a pitch to JAFCO in Tokyo. The underlying business is the same, but the framing, the comparisons, and the risk acknowledgements need to shift.
Ask AI to generate a brief adaptation guide for each investor meeting: what to emphasise, what to downplay, which slides to spend more time on, and which comparables to reference. Feed it what you know about the investor's portfolio, their typical check size, and their stated thesis.
### Step 6: Generate the visual deck
Only now should you move to a presentation tool. Take your polished narrative and slide copy into Gamma, Google Slides, or PowerPoint. AI-powered tools like Gamma can generate initial layouts from your content, but you'll still need to adjust the visual hierarchy, add your own screenshots and metrics, and make sure the data visualisations actually support the claims rather than just decorating them.
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Before you touch any slide tool, open Claude or ChatGPT and give it everything you have. Your one-pager, your internal metrics doc, your previous deck, your product description, your competitive notes. Paste it all in. Then ask for a structured summary of your company's story in the format: Problem, Solution, Why Now, Market, Traction, Business Model, Team, Ask.
This isn't about getting AI to write your pitch. It's about seeing your own story reflected back with fresh structure. You'll immediately notice which sections are thin. If the AI can't produce a compelling "Why Now" from everything you gave it, that's because you don't have one yet.
### Step 2: Build the logic chain before the slide order
Most pitch templates give you a slide order. Slide 1: Title. Slide 2: Problem. Slide 3: Solution. That's fine for structure, but it skips the harder question of whether your argument actually holds together.
Ask AI to evaluate your pitch as a sequence of claims. Each slide makes an implicit promise to the investor, and the next slide should deliver on it. If your problem slide describes a $40 billion market but your traction slide shows $12K in monthly revenue, there's a gap. AI is good at finding these gaps when you prompt it correctly.
### Step 3: Draft the slide content as spoken narrative first
Write each slide's content as what you would actually say when presenting it, not as bullet points. Give AI the context for each slide and ask it to draft 3-4 sentences you'd speak aloud while that slide is up. Then condense those sentences into 2-3 bullet points for the actual slide.
This approach produces much better slide copy than asking AI to "write bullet points for a problem slide." Spoken narrative has natural emphasis and flow. Bullet points written in isolation tend to be generic.
### Step 4: Stress-test every claim
This is where AI pays for itself. Take every quantitative claim in your deck and ask AI to challenge it. "We're targeting a $15 billion TAM in Southeast Asian digital payments." Is that credible? Where does that number come from? How do investors in this space typically react to that sizing? What would a sceptical Series A investor push back on?
You want AI to play the role of a well-informed but slightly hostile investor. Claude is particularly good at this if you set the right system context. ChatGPT tends to be more encouraging, which isn't what you need here.
### Step 5: Create investor-specific variations
This is the step most founders skip, and it matters enormously in Asia. A pitch to East Ventures in Jakarta should emphasise different things than a pitch to JAFCO in Tokyo. The underlying business is the same, but the framing, the comparisons, and the risk acknowledgements need to shift.
Ask AI to generate a brief adaptation guide for each investor meeting: what to emphasise, what to downplay, which slides to spend more time on, and which comparables to reference. Feed it what you know about the investor's portfolio, their typical check size, and their stated thesis.
### Step 6: Generate the visual deck
Only now should you move to a presentation tool. Take your polished narrative and slide copy into Gamma, Google Slides, or PowerPoint. AI-powered tools like Gamma can generate initial layouts from your content, but you'll still need to adjust the visual hierarchy, add your own screenshots and metrics, and make sure the data visualisations actually support the claims rather than just decorating them.
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What This Actually Looks Like
The Prompt
I'm the CEO of LendFlow, a Singapore-based fintech startup. We provide embedded lending APIs that let e-commerce platforms (like Shopee and Lazada sellers, plus regional D2C brands) offer buy-now-pay-later and working capital loans directly within their checkout and seller dashboards. Key facts: - Founded 2023, raised $2.4M seed from Insignia Ventures and angel investors - Live in Singapore and Indonesia, launching Philippines Q2 2026 - 340 merchant partners, $18M in loans facilitated, 2.1% default rate - Revenue: $47K/month (net interest margin + platform fees), growing 22% MoM - Team: 14 people, co-founders ex-Grab Financial and ex-Funding Societies - Raising Series A, targeting $8-12M I'm pitching to Vertex Ventures SEA next week. They typically invest $5-15M in Series A, focus on fintech and enterprise SaaS in Southeast Asia, and have portfolio companies including Grab, Patsnap, and FirstCom Academy. Write slide-by-slide narrative content (what I'd say aloud for each slide) and then condense into bullet points. Also flag any claims that a sceptical investor would challenge, and suggest how to address each one.
Prompts to Try
Prompt 1: Narrative stress test
Here is my current pitch deck content [paste your slide text]. Act as a sceptical Series A investor who has seen 200 pitches this year in [your sector] across Southeast Asia. For each slide, identify: 1. The implicit claim being made 2. The strongest objection a well-informed investor would raise 3. How to address that objection (what data or framing would satisfy them) Be specific and direct. Don't soften the feedback.
What to expect: A slide-by-slide breakdown with pointed criticism. Claude tends to be more direct with the critical feedback than ChatGPT. You'll get 5-8 specific objections you hadn't considered, plus concrete suggestions for addressing each one.
Prompt 2: Investor-specific pitch adaptation
I'm pitching [company description, 2-3 sentences] to [investor name]. Here's what I know about them: - Typical check size: [amount] - Portfolio focus: [sectors/stages] - Notable portfolio companies: [list 3-5] - Based in: [location] Here's my standard pitch narrative: [paste your core deck content] Generate an adaptation guide: which points to emphasise, which to minimise, what comparisons from their portfolio to reference, and any cultural or structural considerations for this specific meeting. Keep it to one page.
What to expect: A concise brief you can review 30 minutes before your meeting. The portfolio comparison suggestions are usually the most useful part, as they give you natural "you already understand this model because you backed X" reference points.
Prompt 3: Market sizing pressure test
I claim my total addressable market is [your TAM figure] for [your market]. My calculation method: [describe how you got the number] Challenge this number from three angles: 1. Is the top-down methodology sound? 2. What does the bottoms-up calculation look like? 3. What would a bear case investor argue the real serviceable market is? Use publicly available data for Southeast Asian markets where possible. Show your working.
What to expect: A structured analysis that either validates your number or (more likely) gives you a more defensible alternative. AI tools with web access (ChatGPT with browsing, Gemini) will pull in recent market reports. Claude will reason through the methodology more rigorously but won't cite live data unless you provide it.
Common Mistakes
Asking AI to "make a pitch deck" from scratch.
This produces generic template content that any experienced investor will recognise immediately. AI should help you refine your existing story, not invent one. Start with your own messy notes and raw data, then use AI to structure and stress-test them.
Using AI-generated market statistics without verification.
AI models frequently produce plausible-sounding market size figures that are either outdated, fabricated, or pulled from a different geographic scope than you need. Every number that appears in your deck needs a verifiable source. Use AI to find the right questions, not to generate the answers.
Creating one deck for all investors.
Founders often treat their pitch as a fixed document. In reality, the best fundraisers have 3-4 variations tuned to different investor types. AI makes creating these variations fast. The cost of not adapting is a meeting where you spend 15 minutes talking about Singapore unit economics to a Jakarta-based investor who cares more about your Indonesia expansion timeline.
Over-polishing the language and under-preparing for questions.
A deck with perfect copy that falls apart under two follow-up questions is worse than a rough deck delivered by a founder who clearly understands every number. Spend at least as much time using AI to simulate Q&A as you spend on the slides themselves.
Ignoring regional investor expectations.
Japanese corporate VCs typically want more technical detail and longer relationship-building before a decision. Singaporean VCs often move faster but scrutinise unit economics more aggressively. Chinese investors may focus on speed-to-market and competitive moats. Australian investors entering SEA tend to benchmark against their home market metrics, which can be misleading. AI can help you prepare for each of these patterns if you give it the right context.
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Tools That Work for This
Claudeis the best option for narrative development and stress-testing. Long context window handles full deck content easily, and it's more willing to give direct critical feedback than other models. Limited by not having live web access in the standard version.
ChatGPT (with browsing)works well for market research prompts where you need current data pulled from reports and articles. The browsing feature is genuinely useful for verifying market sizing claims. Tends to be more encouraging than critical in feedback, which you need to account for.
Gammagenerates presentation layouts from text content quickly and produces better default designs than Google Slides templates. Not a substitute for custom design work on a high-stakes deck, but a fast starting point. Useful for internal versions and early-stage pitch practice.
Geminihas strong integration with Google Workspace, so if your data lives in Sheets and Docs, it can pull context efficiently. Its market analysis capabilities have improved significantly. Worth using as a second opinion alongside Claude or ChatGPT.
PromptAndGo.aican help you refine and store the specific prompts that work for your fundraising process, so you're not rebuilding your investor adaptation prompts from scratch each time you have a new meeting.
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Frequently Asked Questions
AI won't replace the human elements of fundraising, such as warm introductions, personal chemistry, and the trust that comes from a strong track record. What it does well is the preparation work: building tighter narratives, finding gaps in your logic before investors do, and quickly adapting your pitch angle for different audiences. The founders who raise well are the ones who walk in prepared. AI makes preparation faster.
No. Use AI to pressure-test projections you've already built. Feed it your model's assumptions and ask it to identify which ones are most likely to draw scrutiny. Have it generate the questions an investor's associate would ask during due diligence. But the actual numbers need to come from your own model, built on your real data and defensible assumptions.
Start with your own words. Record yourself explaining your company to a friend for five minutes, transcribe it, and use that as your raw input. The AI then helps you structure and refine your natural way of talking about the business, rather than generating corporate pitch-speak from scratch. Also, any slide that uses phrases like "cutting-edge solution" or "AI-powered platform" should be rewritten to describe what you actually do in plain language.
Yes, meaningfully so. In Southeast Asia, investors are used to seeing regional expansion plans with market-by-market rollout timelines. In Japan, expect to provide significantly more detail on technology architecture and risk mitigation. In Korea, the competitive landscape analysis matters more than in most other markets. In Australia (for funds with APAC mandates), you'll often need to spend more time on the basics of the Southeast Asian market itself since the investor may be less familiar with the operating environment. Use the investor adaptation prompt above to prepare for each of these contexts specifically.
If you have your core content ready (financials, product details, market research), the AI-assisted workflow described here takes about 4-6 hours for a complete first draft with investor-specific variations. Compare that to the typical 2-3 weeks most founders spend going back and forth on decks. The time saving is real, but most of it comes from the narrative structuring and stress-testing steps, not from generating slide text.
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Next Steps
The workflow above gets you from raw materials to a stress-tested, investor-adapted pitch deck. If you're earlier in the process and still working out your company story, start with [INTERNAL LINK: How to Use AI to Write a Compelling Company Narrative]. If you've already raised and need to build board materials and investor updates, see [INTERNAL LINK: How to Use AI for Investor Reporting and Board Updates].
Want to customise these prompts for your specific use case? PromptAndGo.ai can optimise any prompt for your platform and audience.
Want to customise these prompts for your specific use case? PromptAndGo.ai can optimise any prompt for your platform and audience.