We’re happy to share the latest in AltsTech’s series profiling how investment managers are using AI, tech, and analytics to generate alpha. We’re fortunate to interview Brian Wong, GP of Ascii Ventures.
David Teten: Please give us an overview of your firm.
Ascii Ventures is a pre-seed venture firm focused on what we call “boringtech” – infrastructure, industrial, workflow, compliance, stablecoin, and AI-enabled businesses that become inevitable over time because they quietly improve how industries operate.
We invest very early, typically at the first institutional round, and spend a lot of time helping founders think through distribution, partnerships, and acquisition pathways. Our portfolio spans heavy industry AI, fintech infrastructure, stablecoin tooling, enterprise software, and marketplaces.
One area we’ve leaned into heavily recently is the intersection of stablecoins, AI infrastructure, and enterprise adoption. We think there’s a massive opportunity in the “picks and shovels” layer supporting the next decade of financial infrastructure.
We also built what we call our “Action Board” – a network of 100+ Fortune 1000 executives and operators who help founders with customer introductions, enterprise validation, and eventual strategic outcomes. For very early-stage companies, distribution and credibility often matter more than capital.
David Teten: Who are your peers/competitors, and how do you differ?
We probably sit somewhere between a traditional pre-seed fund and an operator network that actively fights alongside founders in the earliest stages.
A lot of venture firms provide capital and strategic advice. We try to help founders get their first few meaningful customers as quickly as possible – often the first three enterprise customers that create momentum, references, and credibility. At the earliest stages, speed matters more than perfection.
We also specifically like backing founders who came directly from incumbent industries. Some of the best industrial AI founders aren’t “career startup people” – they’re former operators from logistics companies, manufacturing firms, banks, compliance organizations, or infrastructure businesses who experienced the inefficiencies firsthand. That gives both them and us an edge because they deeply understand how these legacy systems actually function and where the pain points really are.
We spend a lot of time in categories that may initially look unsexy but become inevitable over time – stablecoin infrastructure, industrial AI, compliance tooling, workflow software, and operational infrastructure.
A surprising amount of venture success is still about helping founders get in front of the right decision-maker faster.
David Teten: What’s your background? How and why are you in your role today?
Before Ascii Ventures, I co-founded Kiip, a mobile advertising and rewards platform that raised over $35M from firms including American Express Ventures, Verizon Ventures, and True Ventures before being acquired.
I’ve also spent years angel investing in 30+ companies across consumer, infrastructure, and fintech startups. Over time, I found I was spending more and more of my time helping founders with positioning, partnerships, fundraising, and enterprise strategy.
Ascii Ventures became a natural extension of that work. I enjoy working very early with technical founders who are building foundational infrastructure businesses that may not initially look flashy, but become deeply embedded into how industries operate.
David Teten: What are the tools you’re using for your front office: sourcing, LP relations, investing analysis, etc.? What are the strengths and weaknesses of these providers?
For sourcing, I spend a huge amount of time on LinkedIn, probably more than most VCs would publicly admit. It’s still one of the best places to identify emerging founders, operator movement, and industry shifts before they fully crystallize.
I also use tools like Yutori agents to monitor emerging companies and categories. For example, I built these agents: boringtech companies that have raised pre-seed and seed rounds, and tracking boringtech companies that have recently raised rounds and their news.
The challenge with sourcing is that once a company has already raised a major round or everyone is talking about it online, it’s usually too late to generate differentiated returns.
The goal is less “finding what’s hot now” and more identifying patterns early enough to make educated guesses about what becomes important next. For example, if agentic payments are hot now, perhaps agentic payment fraud prevention would be hot next.
Beyond that, I use ChatGPT and Claude constantly for research synthesis, framing, brainstorming, and diligence acceleration. AI is extraordinarily useful for compressing information gathering, but judgment and taste still matter more than raw information access.
David Teten: What are the tools you’re using for supporting your portfolio companies? What are the strengths and weaknesses of these providers?
Honestly, it’s mostly iMessage, WhatsApp, Slack, and Fyxer AI to make sure I don’t miss important inbound communication.
I don’t really believe in heavily automating founder support. If a founder needs me, I want to be reachable immediately. A lot of the value at the earliest stage comes from responsiveness, urgency, and trust.
The best support infrastructure is often just being present and answering quickly.
David Teten: What technologies/databases have you found helpful in winning LPs?
Honestly, the golf course still works pretty well – hah! [Teten note: he’s joking. Golf is not a big sport in tech anymore.)
But operationally, I use Superhuman heavily to maintain consistent communication cadence with LPs, share updates, and give them a bit of FOMO around the portfolio.
Fundraising at the early-stage VC level is still incredibly relationship-driven. Technology helps maintain consistency and responsiveness, but LPs ultimately back people they trust and enjoy spending time with.
David Teten: What tools do you find helpful for expediting due diligence?
AI tools are extremely useful for accelerating market research, competitive analysis, customer synthesis, and technical diligence.
But I still require an in-person meeting with founders before making investments. A huge amount of conviction comes from understanding how someone thinks, how they react under pressure, and whether they can recruit people into a difficult vision over many years.
Technology can accelerate diligence, but it can’t fully replace intuition and human judgment.
David Teten: What are the tools you’re using for your middle office: tracking, risk management, etc.?
Honestly, our law firm does a large amount of the heavy lifting operationally. We intentionally try to keep our infrastructure lean and avoid unnecessary operational complexity at this stage.
David Teten: What are the tools you’re using for your back office: settlements, records maintenance, accounting, human resources, etc.? What are the strengths and weaknesses of these providers?
We use NAV Fund Administration Group for fund administration and back-office support. One reason we selected them is because they support LP stablecoin commitments, which we think becomes increasingly important over time as digital assets become more normalized within venture infrastructure.
David Teten: A huge amount of valuable data flows through your pipes. What are you doing to capture that data and mine it? Can you share any patterns you have identified?
A lot of it increasingly flows into the way I train and interact with my AI systems, including tools like Supercarl.ai. Specifically, I use Supercarl to find folks in my network who have recently left their large Fortune 1000 companies and either are on a break or have decided to add “Stealth” or consulting to their profile.
I wouldn’t describe what we do as “mining data” in the traditional sense. It’s more about building contextual memory and pattern recognition over time.
The interesting part of AI isn’t simply scraping the internet faster; it’s giving your systems enough context, relationships, and accumulated intuition that they begin generating their own forms of alpha.
David Teten: Do you see any room to use AI to exploit your dataset? If so, what are you doing to move that forward?
I actually think “exploiting datasets” is the wrong framing.
The interesting part of AI is the dance between human context and machine synthesis. If you give an AI enough differentiated context, relationships, pattern recognition, and judgment over time, it starts surfacing insights that aren’t simply derived from public web searches.
That’s where things become interesting.
David Teten: What are the most creative or unusual ways you’re using AI & analytics in your organization?
One of the more useful things I’ve built is essentially a pseudo-LinkedIn MCP internally – a way to structure relationship intelligence, founder movement, ecosystem shifts, and social context into something much more queryable and useful operationally.
That’s probably been one of the highest ROI internal AI projects we’ve done. I can tap into my network of 30,000 contacts and find mutually beneficial connections to my portfolio.
David Teten: What are your unmet technology needs? Places in your firm where you’re seeking a solution and haven’t found an appropriate one?
I still think there’s whitespace for better venture infrastructure tooling, but I also think there’s a danger in over-automating venture capital.
If the perfect AI-native VC operating system existed, eventually venture firms would just become people sitting behind dashboards pressing “yes” or “no.”
There’s still something incredibly important about the manual nature of relationships, intuition, trust-building, and conviction formation. I wouldn’t want to lose that entirely.
David Teten: What processes are you focused on improving?
The two biggest areas are intro velocity and follow-up speed.
A huge amount of venture outcomes come down to how quickly you can connect the right people together before momentum disappears.
I’m also very interested in better ways for VCs to privately share deal flow and opportunities with each other while preserving the exclusivity and personal feel of a trusted iMessage thread.
Most existing systems feel too much like mass distribution or noisy group chats. The magic is often in the curated, trusted, one-to-one nature of the introduction.
