Summary of Founder-Led Sales: Landing Instacart & LinkedIn Without a Sales Team | Nexla

Overview of Founder-Led Sales: Landing Instacart & LinkedIn Without a Sales Team | Nexla

This episode of the SaaS Podcast (host: Omer Khan) features Saket Saurabh, co‑founder of Nexla, a data unification platform that connects fragmented enterprise data across systems, formats, and models. Saket walks through starting Nexla in 2016, founder‑led enterprise sales (first customer: Instacart), product strategy, pricing and contract learning, a painful mid‑stage reset to preserve runway, and how AI reshaped their product (including a conversational data‑engineering tool called Express). Nexla today serves 50+ enterprise customers (DoorDash, LinkedIn, Autodesk, Instacart), ~100 employees, has raised ~$33M, and was cash‑flow positive and multi‑seven‑figures in revenue by Series A.

Key takeaways

• Thesis‑first GTM: Target enterprise early to design for true data complexity (mainframes to modern systems) rather than optimizing for SMB simplicity.
• Founder‑led selling is invaluable: Founders learn product–market fit, pricing, and customer signals faster by doing the early sales themselves.
• Early adopter discovery is human and networked: look for signals (case studies, public posts) and use warm intros; approach conversations as learning, not pitching.
• Create “magical moments”: rapid demos or live fixes (Saket’s team live‑coded a fix in an Instacart meeting) win trust and momentum.
• Pricing heuristic: benchmark against internal build cost — position your SaaS as a fraction (e.g., 1/5–1/10) of the cost to build & maintain in‑house.
• Discipline in hard times: founders skipping salaries, significant downsizing, and tying hires to new revenue helped Nexla become cash‑flow positive while scaling revenue.
• AI accelerates capabilities: prebuilt general models sped up features; Nexla built Express (conversational data engineering) and expanded to documents/videos to serve AI/agent consumers.

Guest background (Saket Saurabh & Nexla)

• Saket’s prior experience: entrepreneur in mobile/ad serving (acquired), product/engineering at NVIDIA.
• Founding impetus: the hard, recurring “data variety” problem observed across ad and partner ecosystems — make data usable at point of use.
• Company profile: Nexla (data unification & pipeline platform) — enterprise focus, ACVs in six figures+, >50 customers, ~100 employees, $33M raised.

Early GTM & founder‑led sales

• Why enterprise first: fragmentation scales with company complexity; designing for large, messy environments ensures product depth and avoids building for the wrong use cases.
• Prospecting approach: warm intros, targeted list of companies that handle diverse ecosystem data (Instacart fit the thesis), conversations framed around learning: “do you see this problem?” not “buy this.”
• Finding early adopters: signals include people who collaborate with startups, public posts, or who are vocal about innovation; no magic list—use network + research.
• Selling style: consultative/technical — earn trust with listening, quick iterative demos, and problem solving. This is perceived less as “sales” and more as partner/problem solving by technical buyers.
• Example: Live coding a data fix during an Instacart session created immediate credibility and an “aha” that helped close.

Product & technical approach

• Core idea: build intelligence to understand incoming data (schemas, entities, naming differences) so variety can be normalized and converged into a usable form.
• Platform design: engineer for production readiness and iterability — small adjustments to show working results quickly to customers.
• Product expansion: moving beyond structured data to documents and video processing; creating capabilities aimed at AI/agent consumers who need clean, contextualized data.
• Express: a conversational interface that translates intent into data pipelines and production‑ready artifacts, lowering the bar for non‑expert users and data engineers.

Pricing, contracts & enterprise mechanics

• Early learning curve: founders initially lacked formal procurement/PO knowledge and learned by doing and getting advice from peers.
• Pricing logic: estimate total internal cost to build/maintain the solution and price as a meaningful fraction of that cost (value‑based approach).
• Negotiation: iterate pricing across deals, ask customers what it costs them today, and use those responses to calibrate willingness to pay.
• Contracts: build experience around enterprise expectations (SLA/responsiveness, support model) and demonstrate you’ll “have their back” (operational reliability).

Surviving, resetting, and scaling efficiently

• Mid‑stage challenge: after initial wins and hiring, growth stalled—company downsized and founders cut pay to extend runway.
• New pact: only hire when new revenue justified headcount; stay lean and iterate product quickly with customers.
• Result: revenue grew faster than spend, leading to multiple seven‑figure ARR and cash flow positivity by Series A.

AI’s impact & product evolution

• Acceleration: prebuilt AI models reduced months of ML work into faster feature delivery.
• Capability shift: AI enabled conversational tooling (Express) that composes data pipelines and produces production‑ready outputs.
• Market implications: startups building AI products still hit enterprise fragmentation when scaling; Nexla positions as a component that lets them focus on core AI value rather than plumbing.
• Broader data support: added document and video ingestion to serve a wider set of AI/agent use cases.

Notable quotes & advice

• From a seed investor: “To build a company, it takes a builder, a seller, and a profit.”
• Jensen Huang’s cafeteria advice to Saket: “If you're not on the critical path, get on it. And if you're on the critical path, get off it.” (interpretation: be involved where you add most value; step away when your involvement blocks scaling).
• On founder selling: “Unless a founder goes and actually sells deals on their own, you don't really fully get to connect the dots.”

Practical recommendations / action items for founders

• If solving complex enterprise problems, start with enterprises to learn real depth; design for complexity first and simplify later for SMBs.
• Do founder‑led sales early: listen more than pitch; treat conversations as product research.
• Use network and public signals to find early adopters; ask about current costs to calibrate pricing.
• Create rapid, tangible demos—even live fixes—to generate trust and momentum.
• Be conservative with hiring and tie hires to recurring revenue during uncertain stages.
• Leverage AI to accelerate ML features; consider building conversational or automated tooling for repeatable engineering tasks.
• Maintain close follow‑up cadence with prospects (product updates, feature relevance) — timing often determines conversion.

Resources & contact

• Nexla: nexla.com
• Saket Saurabh: best reached via LinkedIn (host will link in show notes)

This summary captures the core lessons from Saket’s journey: thesis‑driven enterprise GTM, the value of founder‑led selling, disciplined operations through downturns, and leveraging AI to productize data engineering workflows.