Clodo Thinks It Can Out-Apollo Apollo and I Have Seen Enough to Take That Seriously

The Macro: The Sales Intelligence Market Is Huge, Stale, and Begging for Disruption

I have used Apollo. I have used ZoomInfo. I have used LinkedIn Sales Navigator. I have used Clay. I have built ICP filters with boolean logic that made my eyes cross. I have exported CSVs with 10,000 contacts, enriched them through three different tools, uploaded them to a sequencing platform, and watched the open rates settle at a depressing 18%.

This is the current state of the art in B2B sales intelligence. It works, technically. You define filters. You get lists. You send emails. Some of them land. The process has not fundamentally changed in a decade. The databases got bigger. The UI got cleaner. The pricing got more expensive. But the core workflow of building static lists from categorical filters and then blasting them with templated sequences is the same thing we were doing in 2016.

Apollo has become the default for startups and SMBs because it is cheap and the database is surprisingly good for the price. ZoomInfo dominates enterprise because procurement teams trust the brand and the data coverage is broad. LinkedIn Sales Navigator has the unique advantage of being built on top of the professional graph itself. Clay is the new entrant that lets you chain enrichment sources together like building blocks, which is clever but still fundamentally a tool for building lists.

The problem with all of them is the same. They treat lead generation as a filtering exercise. You know what you want, you express it as a set of constraints, and the tool returns matching records. This works when your ICP is simple and well-defined. It breaks down when what you actually want is nuanced, contextual, or based on signals that do not fit neatly into dropdown menus.

“I want to find VP-level people at Series B SaaS companies who recently hired a data team and are probably evaluating observability tools” is a perfectly reasonable sales intent. No existing tool lets you express it that way and get useful results.

The Micro: Describe Your Buyer, Get Your Pipeline

Sid Rajaram and Rithvik Chuppala built Clodo through Y Combinator’s Summer 2025 batch with a product thesis that is easy to state and hard to execute. You describe your ideal customer in natural language. Clodo’s AI searches across hundreds of data sources, scores and ranks the results by fit using 50-plus signals, and delivers enriched leads ready for outreach.

That sounds like what everyone in sales AI claims to do. The difference, as far as I can tell from actually looking at the product, is in the depth of the intent scoring. Clodo is pulling signals from funding rounds, job postings, hiring patterns, tech stack changes, social media activity, blog posts, and public records to build a multi-dimensional picture of each lead. This is not “company has 50 employees and is in SaaS.” This is “company just raised a Series A, posted three engineering roles in the last month, adopted Snowflake based on their job requirements, and their VP of Engineering tweeted about scaling challenges.”

The numbers they are reporting are early but interesting. Over 128,000 leads discovered on the platform, a 4.9-star rating on the Chrome Web Store, and user testimonials claiming they booked demos within hours of starting. One user mentioned a potential million-dollar ARR contract sourced through Clodo. Testimonials are not data, but they indicate product-market fit signals that are hard to fake.

The outbound automation layer is where it gets competitive with the sequencing tools. Clodo does not just find leads. It generates personalized emails based on the research it did during discovery, schedules multi-step sequences across day one, three, and seven, and handles follow-ups automatically. This puts it in direct competition with not just Apollo and ZoomInfo for data, but also Outreach, Salesloft, and Instantly for execution.

Pricing is $125 per user per month for the standard tier, which includes up to 200 leads. That is roughly in line with Apollo’s mid-tier pricing and significantly cheaper than ZoomInfo. The enterprise tier is custom.

The Chrome extension as an outbound copilot is a smart distribution play. Sales reps live in their browsers. Meeting them there with a tool that can research and compose outreach in real time while they are browsing LinkedIn or a prospect’s website is the kind of workflow integration that drives daily active usage.

The Verdict

The sales intelligence market is enormous and the incumbents are complacent. Apollo has not meaningfully innovated in two years. ZoomInfo’s moat is its database, not its product experience. LinkedIn Sales Navigator is designed to keep you on LinkedIn, not to actually help you close deals. There is room for an AI-native entrant that rethinks the workflow from scratch.

At 30 days, I want to see the data quality. How accurate are the enriched profiles? What is the email deliverability rate on leads sourced through Clodo versus Apollo? Data quality is the game. Everything else is UI.

At 60 days, the retention numbers matter. Sales tools have notoriously high churn because reps switch jobs, teams restructure, and the shiny new tool loses its shine. If Clodo can show strong 60-day retention, it means the AI layer is delivering ongoing value, not just a novelty effect.

At 90 days, the competitive response will tell us a lot. If Apollo adds a natural language search feature in the next quarter, that is validation. If ZoomInfo acquires an AI startup to bolt on intent scoring, that is also validation. The question is whether Clodo can build enough of a lead before the giants react.

I think the natural language approach to lead discovery is the right abstraction. The current filter-based paradigm is a product of database limitations, not user preferences. Nobody actually wants to build boolean queries. They want to describe their buyer and get a pipeline. Clodo is building for how sales should work, not how it has worked. That is usually a good sign.