The Hog wants to be the one API that AI agents ask about the web

There is a particular kind of mess that every growth team eventually accumulates. A Clay account here. An Apollo seat there. An Exa key someone spun up for a prototype, a Tavily key for another, a scraper held together with a cron job and hope. Each tool solves one slice of the same question - who are these people, what do these companies do, what is being said, and where - and each one bills separately, breaks separately, and returns data in its own shape.

The Hog, a company in Y Combinator's Fall 2025 batch, is a bet that this mess is the product opportunity. Its pitch fits on one line: "One API to search, enrich, and monitor the web." Instead of wiring up five vendors, a developer calls a single endpoint, and The Hog decides where to get the answer.

That framing matters more now than it would have two years ago, because the buyer has changed. The customer is increasingly not a person clicking through a dashboard but an AI agent making a request in the middle of a task. Agents need data on demand, in a predictable format, without a human to reconcile three conflicting exports. The Hog describes itself on Y Combinator's site as a "real-time web intelligence API for AI agents and GTM teams." Both audiences want the same thing: one reliable place to ask about the web.

01 / What it doesOne endpoint, many sources

Under the hood, The Hog is an aggregation layer. It unifies people search (role, seniority, company), company search (firmographics, tech stack, buying signals), general web search, social search across X, Reddit and TikTok, sentiment scoring, contact enrichment with verified emails and mobile numbers, competitor monitoring, multi-hop deep research, and scraping of sites like LinkedIn and Instagram. Results can come back as JSON, markdown, CSV, XLSX, or plain language.

The interesting design decision is what happens when you ask. Rather than pointing you at a single provider, The Hog routes each request through multiple data sources using what it calls waterfall logic: try the first source, and if it comes back thin, fall through to the next, and the next, until something good returns. The caller never sees the retries. They see one answer.

How a single request resolves

Your agentone request

→

The Hogwaterfall router

→

Best sourceone clean answer

Provider A

no match ↓

Provider B

partial ↓

Provider C

verified ✓ returned

02 / Who it is forAgents first, growth teams close behind

Two groups sit at the center of The Hog's market. The first is developers building AI agents, who need a data backbone their agents can call without a human babysitting the output. The second is the people who have always lived in this data: sales, marketing, and growth teams at startups and B2B software companies, running outbound, enriching leads, and keeping an eye on competitors.

The everyday jobs look familiar - find the right accounts, get a verified email, learn where a target audience actually spends its time, watch when a rival ships or stumbles. What changes is the plumbing behind them. The Hog's argument is that the same API can serve a script written by an engineer and a workflow run by a marketer, because both are really just asking the web questions.

03 / The problemStale databases and saturated channels

Two problems show up repeatedly in how The Hog describes the space. The first is freshness. A lot of sales-intelligence tooling reads from databases that were accurate last quarter. For a market moving on live signals - a hiring spike, a product launch, a thread blowing up on Reddit - last quarter is a lifetime. The Hog leans on live signals with timestamp tracking rather than a static snapshot.

The second is saturation. The default outbound channels, email and LinkedIn, are crowded. Standing out requires knowing where an audience gathers before everyone else floods in. That is why social listening across LinkedIn, Reddit, X and forums sits alongside the enrichment features: the point is not just who to contact, but where the conversation is actually happening.

04 / How it is differentConsolidation as the feature

The Hog is refreshingly plain about its competitive set: it names the tools it wants to absorb. On its Y Combinator profile it says the API "eliminates the need for separate integrations with Clay, Apollo, Exa, Tavily, and similar tools." So the competitors are also, in a sense, the ingredients. The differentiation is not a single capability none of them has - it is the consolidation itself, plus the waterfall routing that turns many uneven sources into one dependable response.

That is a defensible position if the aggregation genuinely holds up, and a fragile one if any single provider could be swapped in directly. The bet is that maintaining one integration, with sensible fallbacks, beats maintaining five - and that most teams would rather not think about which vendor has the best coverage on any given day.

05 / The business modelPay for calls, not seats

The pricing is usage-based, and the choice says something. There are no tiers and no seat limits. The first 500 calls each month are free, then you pay per call, with rates that vary by what you are asking for. Charging by usage rather than by login is a quiet vote of confidence: it only works if people keep calling because the answers keep being worth it.

Call type	Approx. rate
Company search	$5.18 / 1k calls
People search	$6.57 / 1k calls
Web search	$3.29 / 1k calls
Verified email	$0.065 / match
First 500 calls / month	Free

Rates as published on thehog.ai; enterprise plans available. Figures approximate and subject to change.

Before it settled into API-first pricing, The Hog wore a different jacket. Its Y Combinator launch introduced it as an "AI-native go-to-market command center" with sales and marketing co-pilots that map ideal customer profiles, generate ranked action plans, and monitor the competitive landscape - even, at one point, a guarantee framed around finding a qualified customer within a set window. That command-center vision did not disappear so much as sink one layer down: the API is the data foundation the co-pilots were always standing on.

06 / The peopleA repeat first-hire and an early AI engineer

The Hog was founded in 2025 by Hudson Liao and Paulo Nascimento. Liao, the CEO, is a growth operator with close to 15 years in go-to-market work, and a specific kind of resume: he has been the first growth or marketing hire multiple times over. On The Hog's YC profile he is credited with scaling one startup as a solo growth hire and helping another reach profitability with only a couple of months of runway left. Building the same playbook by hand that many times is a plausible origin story for wanting to ship it as infrastructure.

Nascimento, his co-founder, comes at it from the engineering side, with early AI experience including work as an early generative-AI hire at Auth0. The team is small - Y Combinator lists two people, and public listings put the broader headcount around five as it hires engineers. It is a reminder that a two-person company can now ship the kind of data infrastructure that used to require a department.

07 / Where it fitsThe boring, load-bearing layer

Step back and The Hog sits in an unglamorous but important spot: the data layer beneath the current wave of AI agents. Chatbots and copilots get the attention, but they are only as useful as the facts they can reach. Someone has to supply fresh, structured knowledge about people, companies and conversations, in a shape a machine can consume. That is the job The Hog is auditioning for.

Whether it wins comes down to two unglamorous questions. Does the aggregated data actually beat any single provider often enough to justify the middle layer? And does usage-based pricing scale into a real business as agents make more and more calls? Those are open questions for a company this young. What is clear is the shape of the bet: not a flashier interface, but fewer integrations to babysit - one endpoint where there used to be five.