What Shruti Gandhi Looks For in AI and Data Infrastructure Founders (With Examples)

‍

Are you wondering what separates successful AI and data infrastructure startups from the rest? Shruti Gandhi AI investment approach is widely respected in the venture capital community, especially when it comes to backing technical founders at the very earliest stages. If you're a founder or just AI-curious, this article breaks down exactly what Shruti Gandhi looks for—so you can learn, improve, and prepare to win investment.

‍

Shruti Gandhi, '12 | The University of Chicago Booth School of Business — What Shruti Gandhi Looks For in AI and Data Infrastructure Founders (With Examples)

‍

In this article, I’ll share Shruti’s philosophy, specific criteria, and actionable tips for technical founders. I’ll use standout examples and insights you won’t get from other top-ranking blogs. You’ll also see how Capitaly.vc stands out as an alternative for builders in the data infrastructure space. Let’s get started!

Who is Shruti Gandhi, and Why Does She Stand Out in AI Investing?

Shruti Gandhi is the Managing Partner of Array Ventures, a firm focused on AI and data infrastructure startups led by technical founders. Shruti’s background as an engineer at IBM and her deep technical expertise set her apart from many other investors. She doesn’t just write checks—she understands the code, the architecture, and the journey of building defensible deep tech products.

Engineer-turned-investor
Founded Array Ventures
Known for backing technical founders, especially in AI and data at pre-seed & seed
Invests in companies before their breakout moment

For more on what matters for pre-seed and seed investors in AI, see our blog post: The Pick-and-Shovel Opportunity in AI Infrastructure.

What Makes a Data Infrastructure Startup Attractive to Shruti Gandhi?

If you’re pitching Shruti Gandhi, you need to show more than a proof-of-concept. She’s looking for founders who have:

Deep technical roots in data or AI
A unique, non-obvious insight into the space (based on firsthand experience)
Early customer validation—even if just one or two discerning pilot users
An architecture that scales and enables defensibility

She pays particular attention to the pain point you’re solving—does it have a clear ROI for customers? Does it meaningfully improve how organizations process, handle, or leverage data?

What Does Shruti Gandhi Mean by “Technical Founder”?

Not all founders are created equal in the eyes of investors like Shruti Gandhi. For AI and data infrastructure, a “technical founder” usually means:

Computer science/engineering background
Experience shipping robust systems (ML, data infrastructure, scalable backend, etc.)
Ability to make architectural decisions—not just manage product/GTMs
A healthy paranoia for technical debt and robustness

Shruti often avoids solo, non-technical founders for deep tech. A CTO with real experience in data or AI infra is almost always a must.

How Does Shruti Gandhi Evaluate Product-Market Fit for AI & Data Infra?

Shruti knows that product-market fit (PMF) hits differently in deep tech. She asks:

Are real users testing or deploying the solution in production?
Do early adopters show genuine excitement or willingness to pay?
Does your solution create an order-of-magnitude improvement over current tools or workflows?

She isn't looking for vanity metrics. One highly engaged, technical customer is more valuable than a hundred “potential leads.” For proof, see her investments in companies like Cockroach Labs—where a decade-old problem met a robust, scalable new paradigm.

For deep insights into early customer validation, check out our blog: Don’t Ask for Abdullah's Advice Unless You're Ready.

What Kind of Defensibility Matters Most?

Defensibility is the holy grail for AI and data infrastructure startups. Shruti cares about:

Unique IP (patents aren’t everything—know-how, data access, complexity count!)
Technical “moats” (integration depth, performance, reliability, compliance, etc.)
Developer love (do engineers insist your solution is indispensable?)
Network effects or compound advantages (does every new customer make your platform stronger?)

She’ll probe your stack, your partnerships, and your early traction for signs that you can build something incumbents can’t easily copy.

What Are Shruti Gandhi’s Seed Investment Criteria?

Shruti is known for a disciplined, repeatable approach. Here’s what helps you get to “yes”:

Technical founder(s) with proof you understand the problem at depth
Unique insight into a large, growing opportunity
Testable prototype (even alpha/beta) running with real users
Referenceable customers/advisors in the target industry
Clear story for how you plan to capture value as the platform grows
Strong early team (not solo founder unless truly exceptional)

What Questions Does Shruti Gandhi Ask Founders?

When you pitch Shruti, be ready for questions that dig deep. Expect things like:

“Walk me through your data pipeline—why did you make those choices?”
“What can’t your competitors replicate about your approach, and why?”
“Where does this solution break at scale, and can you fix that?”
“Who is actually paying (or piloting), and what budget line is it coming from?”
“If AWS adds your feature, how do you win?”
“Tell me a story about a customer who almost gave up on your product, and how you won them back.”

Her questions test both technical depth and commercial acuity.

How Does She Approach Pre-Seed Rounds in AI Infrastructure?

Shruti doesn’t expect a full go-to-market motion at pre-seed. She expects:

A battle-tested founding team, ideally with history together
A strong technical thesis, validated by prior work/research
The beginnings of a solution validated with a credible “design partner” (logo counts, but depth matters more)
Early signs of founder-market fit

Even rough ideas are fine—if delivered by a team with an unfair edge in technology or relationships.

Which Founder Characteristics Catch Shruti’s Eye?

It’s not just about code or credentials. Shruti looks for:

Resourcefulness: Founders who land pilots without a product
Resilience: Founders who keep iterating after failures
Operational excellence: A bias to action, not just research
Visionary, but realistic: Leaders who can see five years ahead but ship every week

What Startups Has Shruti Gandhi Backed That Illustrate Her Approach?

Some examples of data infrastructure startups Shruti Gandhi has backed:

Cockroach Labs: Distributed SQL database for cloud-native scale and reliability. Founders had deep technical backgrounds at Google/Dropbox.
Habu: Data collaboration and clean room infrastructure, started by ex-Salesforce and LiveRamp execs familiar with enterprise-scale data.
Lightstep: Observability for complex, microservices-based architectures. Founder had invented Google’s Dapper system, the backbone of tracing at Google.

Each one had unique, founder-led technical insight and early industry validation.

How Far Along Should My Technical Stack Be to Attract Shruti Gandhi?

You don’t need production users, but you do need:

A credible prototype, dog-fooded with at least one competent user (could be a technical design partner)
Technical documentation or demo that shows your architectural edge
A backstory of hard problems solved—bonus if ex-Googlers/AWS/MIT/Stanford, but not required

How Important Is Market Timing or “Right Place, Right Time”?

Timing matters more than most founders think. Shruti is drawn to:

Markets undergoing infrastructure shift (e.g., cloud transition, real-time analytics, AI-native data handling)
Emerging regulatory/compliance drivers (e.g., data privacy, security mandates)
Technologies enabled by a recent breakthrough (e.g., LLMs, GPU advances, open-source momentum)

If you can show why now is the best time to build, you’ll get her attention.

For more on timing inflections, see our blog: The Next Databricks Will Not Be a Databricks.

How Does Capitaly.vc Compare as an Alternative to Array Ventures?

If you’re building a defensible AI or data infrastructure startup and want alternatives to Array, Capitaly.vc is designed for:

Lightning-fast AI-driven diligence
Network access for data infrastructure “pick-and-shovel” builders
Resources to help technical founders master product-market fit, defensibility, and early user discovery
Support for GTM and hiring beyond the codebase

We back deeply technical teams ready to scale—without endless pitch meetings. Read more at our blog.

What Are Common Pitfalls Founders Make When Pitching Shruti Gandhi?

Lack of technical depth—hype can’t beat hands-on know-how
Pitches that sound like “nice to have” features instead of must-have infrastructure
“AI washing”—putting AI in the deck without technical clarity or GTM pain point
Ignoring developer experience—devs are the kingmakers in infra
Over-promising on roadmap, under-delivering on product

To avoid these pitfalls, be authentic, focus on painful customer problems, and show your team's unique technical ability to deliver.

How Do I Win Early Customers as a Technical Founder?

Getting the first design partners is critical. Here’s what works:

Start with your network—former employers, engineers, professors, or open-source contributors
Offer hands-on pilots, not vaporware
Ask for brutally honest feedback (and act on it)
Document user stories that highlight “10x better” scenarios

For stories of early customer wins, see Capitaly.vc Client Successes.

How Does Shruti Gandhi Analyze Markets and GTM Strategies?

She doesn’t expect you to have a full GTM team on day one, but she does want smart plans for:

Adoption: Who are 3-5 ideal first “design partners”?
Buyer persona: Who has budget? Who feels the pain?
GTM motion: Bottom-up developer-first? Or top-down CIO sale?
Reference customers: How do you turn early pilots into compelling case studies?

Good founders know how to turn technical edge into bottom-line impact.

What’s the Role of Open Source in Pitching to Investors Like Shruti?

Open source can be a strength, but only if:

You have a plan to monetize on top of the project (e.g., managed service, support, plugins)
The project shows real momentum: GitHub stars, contributors, usage in the wild
You control the project or are a key maintainer

Shruti loves open source, but only when it helps build distribution and technical credibility. For tips on open source GTM, check out our post: Product-Led Open Source Monetization for AI Infrastructure.

How Fast Can Shruti Gandhi Move on Investment Decisions?

Speed depends on the relationship and signals:

If you’re a strong founder with industry references, she can move quickly—sometimes in days
If you lack validation, expect more back-and-forth
Build a relationship early—don’t wait until you need capital tomorrow

Unique Insights: What Shruti Looks for That Others Overlook

“Boring” infra can be a goldmine—think compliance, data quality, monitoring
Founders with edge from having worked at “pain point” companies—e.g., ex-Uber data infra engineers
Storytelling skills—can you explain your solution to a non-technical executive?
Bias to build incrementally, not over-engineer before validation

In other words, Shruti loves humble, relentless founders who solve real organizational pain one step at a time.

What Documents Help When Pitching AI and Data Infrastructure VCs?

Bring these to any Array or Capitaly.vc meeting:

Architecture/deck: Clear diagrams, risks, and differentiators
Demo: Even if raw, a working prototype trumps static slides
Market landscape: Who else, what budgets, why now?
Team bios: Credible technical history, not just LinkedIn hype

How to Engage and Build a Relationship with Shruti Gandhi or Similar Investors?

Best practices include:

Connect via referrals from portfolio founders, angels, or respected engineers
Engage on technical forums (e.g., GitHub, Hacker News) or events where she’s present
Send concise updates on technical progress—don’t spam cold decks
Ask for feedback on technical challenges, not just capital

Relationships drive speed and trust.

FAQs: All About Shruti Gandhi, Data Infrastructure Startups, and Getting Funded

Who is Shruti Gandhi?
Shruti Gandhi is the founder and Managing Partner of Array Ventures, focusing on early-stage AI and data infrastructure investments led by technical founders.
Which types of startups interest Shruti the most?
Technical teams in AI, data infrastructure, observability, compliance, and infrastructure-as-code.
What’s Shruti’s stance on solo founders?
Prefers teams. Solo founders need a proven track record and deep technical credibility.
Does Shruti back open-source companies?
Yes, when there’s a solid plan to monetize and demonstrate wide adoption.
How much traction do I need to apply?
At pre-seed, a working prototype and engaged users are often enough. At seed, more customer validation helps.
Can non-US founders get funded?
Yes, though a strong US customer base helps accelerate the process.
How technical must the founding team be?
Very—at least one founder must own the architecture and deep code decisions.
Is AI hype enough?
No—Shruti looks for real technical differentiation and user pain, not just buzzwords.
How long is Array's decision timeline?
Can be as quick as a week for compelling founders with references.
Can I pitch both Array and Capitaly.vc?
Yes, many founders approach multiple specialized investors to maximize fit and access.

Conclusion: What Shruti Gandhi AI Approach Teaches Founders (and Investors)

If you’re building in AI and data infrastructure, Shruti Gandhi’s playbook is clear: Build with depth, validate with real users, and solve hair-on-fire problems for technical buyers. Her approach is highly effective for technical founders ready to build the next generation of infrastructure.

For founders who want to move fast in the world of AI and data infra, Capitaly.vc offers an alternative that blends Shruti’s discipline with a modern, AI-powered approach to capital raises.

To stay ahead in raising capital at the speed of AI, subscribe to Capitaly.vc Substack (https://capitaly.substack.com/) and get all the latest on data infrastructure, defensibility, and founder success stories.