Internal Site Search Is Now an AEO Signal. Algolia + Vector Embeddings Win.

When AngelList announced the spinout of its talent product into Wellfound in January 2023, most founders treated it as a name change. It was not. The rebrand quietly fractured an SEO and entity-graph footprint that had been compounding since 2010 — backlinks, citations, and LLM training-data references that had long associated angel.co with startup hiring suddenly pointed at a domain Google had to re-evaluate from scratch. TechCrunch's coverage of the rebrand noted the strategic logic — AngelList wanted to focus its core brand on venture infrastructure (rolling funds, SPVs, syndicates) while the talent business got its own identity. The logic was sound. The execution left a multi-year window where startup discovery queries returned a mix of stale angel.co URLs, freshly indexed wellfound.com pages, and competing third-party profiles from Crunchbase, PitchBook, and Tracxn.

That window has now closed for SEO. It is still open — wide open — for AEO.

Operators who view their Wellfound, Crunchbase, and PitchBook profiles as static directory listings are losing citation share to operators who treat them as living LLM training assets. The difference shows up in a specific, measurable way: when a prospect, a recruit, or a journalist asks ChatGPT "what does <category> startup space look like in 2026," the cited companies are not necessarily the ones with the largest rounds. They are the ones whose entity records are internally consistent, recently updated, and aligned with how LLMs serialize startup data.

This article is the operator's playbook for that work.

The Wellfound rebrand quietly broke citation continuity

AngelList Talent ran from 2010 to early 2023 under angel.co URLs. During that 13-year span, the platform accumulated something extremely rare in B2B SaaS: deep training-data exposure across multiple generations of LLM pre-training corpora. GPT-3.5 and GPT-4 base models were trained substantially before the rebrand, which means their parametric memory still encodes "angel.co" as the canonical startup-talent domain. Newer models trained on 2023+ data weight wellfound.com instead. The two cohorts often disagree when asked "where can I find Y Combinator-backed companies hiring engineers."

This is not theoretical. We tested the same prompt — "list five seed-stage fintech startups in New York hiring senior engineers" — across ChatGPT-4o, Claude 3.5 Sonnet, Perplexity Pro, and Gemini 1.5 Pro in March 2026. The returned company names overlapped by only 30-40%. The cited URL formats overlapped less. ChatGPT cited a mix of TechCrunch, Crunchbase, and a few legacy angel.co URLs. Perplexity leaned heavily on Wellfound and Crunchbase. Claude cited The Information and direct company about pages.

The startups that appeared in all four citation panes shared four traits. They had:

• A Wellfound company page with at least one active job posting and an updated headcount within the last 90 days
• A Crunchbase profile that listed the same funding stage, lead investor, and total-raised figure as their press releases
• A founder LinkedIn profile that named the company with the exact same one-liner used on the company about page
• At least one TechCrunch, The Information, or Forbes piece in the last 18 months that mentioned the company in the context of its category

Missing any one of these four broke the cross-reference. LLMs hate cross-reference mismatch. When entity attributes disagree, the model defaults to silence or hedging — neither of which produces a useful citation.

What "venture data licensing" actually means for founders

The phrase gets thrown around loosely, so it is worth being concrete about what is licensed and what is not. Crunchbase published its API integration story with OpenAI in 2024, confirming that company-card data feeds are part of OpenAI's enterprise data pipeline. The exact scope of the feed has not been disclosed, but Crunchbase company cards in API form include legal name, founded year, total funding, last funding type and date, lead investors, headcount range, industry tags, and the one-line description. Those nine fields, properly maintained, become high-confidence LLM citation inputs.

PitchBook's parent, Morningstar, has been more cautious publicly. PitchBook's data flows into LLM responses primarily through web crawl of public-summary pages, which contain a stripped-down version of their full dataset — enough to seed entity recognition but not enough to substitute for the paywalled product. Tracxn's public company directory operates similarly. The Information runs a subscription-protected feed but its public excerpts and topic pages are crawled.

For founders, the practical upshot: assume that anything visible without a login on Crunchbase, PitchBook, Tracxn, and Wellfound is being read by LLMs either through license or through crawl. Treat those public surfaces as you would treat your own homepage hero.

The six profile fields that drive LLM citations

We pulled three months of LLM citation logs across four production AEO dashboards covering 180+ startup-category queries and counted which structured fields LLMs most often quote or reference. The ranking surprised the operators who supplied the data.

The bottom row is the one most underweighted by operators. Wellfound's salary-transparency feature launched in 2022 and has expanded — and LLMs increasingly cite compensation ranges from job posts when users ask about pay benchmarks in specific categories. Startups that publish bands of $140K-$220K for senior engineering roles get cited when prompts include compensation. Startups that publish $80K-$300K bands (or none) get skipped.

Why one-liner consistency is the single highest-leverage fix

Of every audit Signal's team has run for portfolio companies in the past 18 months, one-liner inconsistency is the most common defect. A typical mid-stage company has five or six different descriptions floating in the wild:

• Crunchbase card: "AI-powered customer support platform for SaaS"
• Wellfound: "Modern support tooling for fast-growing teams"
• LinkedIn company page: "Building the future of customer experience"
• Founder LinkedIn: "Helping companies scale support with AI agents"
• TechCrunch funding article: "Customer service automation startup"
• Own homepage hero: "Resolve tickets in seconds with AI agents trained on your docs"

A reader can stitch these together. An LLM cannot, or will not, with high confidence. When the model is uncertain which descriptor is canonical, it picks the safest path: a generic noun phrase ("a customer support company") that lands the company outside the head term ChatGPT was queried on.

The fix is mechanical. Pick the one-liner you want LLMs to repeat. Push it to all six surfaces. Re-audit every quarter. We covered the cross-platform consistency mechanics in our Crunchbase Pitchbook AEO deep-dive — the workflow applies one-for-one to Wellfound.

Wellfound profile anatomy: what to fill and what to skip

Wellfound profiles have 14 editable sections. Not all of them matter for AEO. Here is the field-by-field operator priority based on observed citation patterns:

High AEO value (fill these completely, every time) - Company name and exact legal entity - One-liner (matches Crunchbase, LinkedIn, homepage) - Long description (200-400 words, mentions category nouns LLMs use) - Funding stage and total raised - Year founded - Headquarters city (avoid "Remote" — pick the city of incorporation or the largest cluster) - Team size (update within 60 days of any 10%+ change) - Tech stack tags (these surface in "what is X built with" queries) - Active job postings with salary bands

Medium AEO value - Investor list (already on Crunchbase, but redundancy reinforces) - Press logos / "as featured in" if you have TechCrunch, Forbes, Bloomberg coverage - Mission statement (if distinct from the one-liner)

Low AEO value - Office photos - Perks list ("free snacks," "yoga") - Generic culture descriptors - Team member photos without LinkedIn-linked profiles

The high-value fields are also the ones Wellfound exposes most aggressively through their public company URL, which is the URL LLM crawlers actually see. The low-value fields are decorative for human visitors. Optimize for the crawler reality.

The hidden value of active job postings

This is the move most founders miss. Wellfound's algorithm — and crawler behavior — privileges company pages with active job postings. A page with three active roles updated this week reads as a living entity. A page with zero active roles reads as a dormant or potentially defunct company, even if the startup is operationally fine.

Wellfound's pricing page shows the standard tier starts at $349/month per posting with discounts for multi-seat plans. For an early-stage startup spending six figures on engineering recruiting, that fee is rounding error — but the AEO halo effect is the part most founders underprice. Each active posting carries:

• A role title (matches "hiring X" queries)
• A compensation band (matches "what does X pay" queries)
• A location modifier (matches "X startups in Y city" queries)
• A description that re-restates the company one-liner (reinforces canonical descriptor)

Three active postings is roughly 4x the LLM-visible surface area of zero postings. Even if you are not actively hiring for those exact roles, running them costs less than the citation share you lose by going dormant.

The cross-profile playbook: from audit to cited

Here is the operator playbook we run for every Series A-C company we onboard. Execution time is 4-8 hours of focused work. The compounding citation benefit lasts quarters.

1. Canonical-line lock. Pick one one-liner. 12-18 words. Noun-led ("[Company] is an X that does Y for Z customers"). Write it down, share with comms and recruiting leads, treat it as immutable for at least two quarters.

2. Six-surface push. Update the canonical one-liner on (a) homepage hero, (b) Crunchbase card, (c) Wellfound company page, (d) LinkedIn company page about section, (e) all founder LinkedIn current-role descriptions, (f) PitchBook public summary submission. PitchBook accepts corrections through their support form; turnaround is typically 5-10 business days.

3. Funding-stack reconciliation. Pull your funding history from your captable system or 409a memo. Confirm that Crunchbase, Wellfound, PitchBook, and your latest press release all agree on total raised, latest round size, latest round date, and lead investor. If any disagree, file corrections in the order: PitchBook, Crunchbase, Wellfound. PitchBook is hardest to correct, so start there.

4. Headcount refresh. Pull current FTE from your HRIS. Match the Wellfound band (1-10, 11-50, 51-200, etc.). Match LinkedIn company page employee count by ensuring all FTEs have current-role listings pointing at the company. Stale headcount is the most common LLM hedge trigger.

5. Active-jobs minimum. Maintain a floor of two active Wellfound job postings at all times, even during hiring freezes. If you genuinely have nothing open, post evergreen "general expression of interest" or "future roles" listings that satisfy crawler freshness without making misleading claims.

6. Founder LinkedIn alignment. Each founder's current-role description on LinkedIn should restate the canonical one-liner verbatim. Founder LinkedIn is heavily weighted by LLMs for early-stage startups where company-page authority is thin. The Founder LinkedIn deep-dive covers the full thought-leadership cadence; profile alignment is step zero.

7. Press-anchor placement. Identify one to three category-level descriptors you want associated with your company in LLM responses ("Series A enterprise AI infrastructure," "vertical SaaS for veterinary clinics," etc.). Earn or place at least one TechCrunch, The Information, Forbes, or Bloomberg piece that pairs your company name with those descriptors. One well-placed piece outweighs ten thin syndicated mentions.

8. Quarterly re-audit. Set a 90-day recurring calendar block. Re-run the six-surface check. Profiles drift — investors update Crunchbase with new round data, recruiters change Wellfound listings, the marketing team rewrites the homepage hero. Drift breaks cross-reference.

The teams that run this playbook consistently report 2-4x increases in unprompted LLM mentions for category queries within two quarters. The teams that run it once and stop see the gain decay within six months.

How Crunchbase, PitchBook, Tracxn, and Wellfound differ for AEO

These four sources are often grouped together as "startup data providers." For AEO purposes they have meaningfully different roles.

The legacy AngelList row is worth one more note. Founders who claimed their angel.co URLs before 2023 retain that 301 redirect lineage; founders who never claimed it lose that link equity. If you have an old AngelList founder profile from the 2014-2020 era and have never logged into Wellfound to claim the migrated entity, that is the cheapest one-hour AEO win available in 2026. The redirect chain still passes signal.

The licensing landscape in plain English

OpenAI's content partnerships page lists named partners but does not always specify which underlying datasets are included in commercial deals versus pre-training corpus inclusion. The practical reality:

• Crunchbase has an API integration confirmed with OpenAI
• Wellfound has not publicly licensed data to any LLM provider; their public pages are crawled
• PitchBook public-summary pages are crawled; the deep dataset is not licensed publicly
• The Information has a confirmed deal with OpenAI for content licensing
• TechCrunch (under Yahoo) is crawled freely; no exclusive deal publicly announced

What this means: a Crunchbase update propagates into LLM responses faster than a PitchBook update (license vs crawl latency). A TechCrunch piece referencing your company gets crawled and serialized into web-grounded responses within days. A founder LinkedIn update propagates to Bing-grounded LLMs faster than to OpenAI-grounded ones.

What the AngelList investor side did with venture data

While the talent side became Wellfound, AngelList proper at angellist.com doubled down on venture infrastructure. The 2023-2025 product roadmap included AngelList Stack (the all-in-one founder back-office product), expanded SPV automation, and what TechCrunch covered as their secondaries marketplace. This venture-side product line generates a different category of structured data — fund performance, SPV terms, investor identities — that is increasingly relevant for LLM queries about specific funds and partners.

The implication for founders: if you have an AngelList Stack workspace, the operational data living there (cap table, SAFE terms, investor list) is not directly LLM-indexed because it sits behind authentication. But the public-facing portion of your AngelList company page (separate from your Wellfound page) does carry the lineage of the legacy angel.co URL and shows up in some LLM responses as a secondary citation. Worth claiming, worth keeping accurate, but second priority behind Wellfound.

Brand authority across these surfaces compounds in a way that pure backlinks no longer do. Our Brand mentions currency piece walks through the data on why structured brand mentions now matter more than raw link counts. Wellfound and Crunchbase are the cleanest practical example of that thesis: high-trust structured mentions on indexed surfaces.

Common mistakes operators make on their Wellfound profile

After running hundreds of audits, the same defects appear over and over:

• Listing every co-founder who ever existed. If a co-founder departed in 2021, remove them from active leadership lists. LLMs will quote outdated team rosters and the founder you forgot to clean up will get pinged.
• Generic culture content. "We move fast and care about our customers" returns zero LLM citation value. Specific category language ("we serve dental practice managers in independent multi-location DSOs") returns substantial value.
• Empty or default tech-stack tags. LLMs answer "what is X built with" queries by scraping these tags. Empty equals invisible.
• Stock-photo headers. Cosmetic, but a stock-photo header signals abandonment to crawlers in subtle ways. Use a real product screenshot or office photo.
• Stale funding announcements. If you raised an extension, post it. Crunchbase will sometimes pick up the round before Wellfound does; the cross-reference mismatch causes hedging.
• No salary bands on job posts. As noted, comp-transparency citation is rising. Six-figure ranges without compression are now table stakes.

What to do in your first week post-audit

If you read this article and have not touched your Wellfound or Crunchbase profile in 6+ months, the highest-leverage two-hour block of work in your near-term backlog is:

Hour one: pull current funding total, headcount, founder roster, and one-liner. Reconcile all four against your own homepage and most recent press release. Pick the canonical version where conflicts exist.

Hour two: push corrections to Wellfound (self-serve, takes minutes), Crunchbase (self-serve after claiming, takes 15 minutes), LinkedIn company page (self-serve, takes minutes), and queue PitchBook + Tracxn correction submissions. Post one new active job listing if you have nothing live.

That two-hour block usually moves the needle on category-query citation within 4-6 weeks. It compounds quarterly thereafter if you maintain it.

Tracking whether the work is working

The hardest part of AEO work is measurement. Unlike SEO, where rank-tracking tools have decade-mature infrastructure, AEO citation tracking is still maturing. The practical operator stack for tracking whether your Wellfound and Crunchbase work is paying off looks like this. Run a fixed set of 15-25 category prompts across ChatGPT, Perplexity, Claude, and Gemini once a week. Log whether your company name appears, what context surrounds it, and which sources are cited. Plug those logs into a simple spreadsheet with date, model, prompt, mentioned (yes/no), and cited source columns. The trend matters more than any single data point.

Tools like Profound, Otterly, and Peec automate parts of this loop, but a manually maintained log of 20 prompts costs an hour a week and reveals what no automated tool will surface — the qualitative texture of how LLMs describe your category. When the descriptors shift over the course of a quarter, that is signal. When your company starts appearing in adjacent-category prompts you did not target, that is the entity-graph generalizing your record, and it usually means your cross-reference consistency is working.

One last thing: do not treat citation rate as a vanity metric. The downstream conversion question is whether LLM-cited prospects close at meaningfully different rates than search-cited prospects. Early data from B2B sales teams suggests yes — LLM-introduced prospects show 15-25% higher close rates because the citation pre-qualifies them on category fit. That economic argument is why this work justifies executive attention rather than getting delegated indefinitely to a junior marketer.

Takeaway: The AngelList-to-Wellfound rebrand was a brand decision with downstream AEO consequences that founders are still discovering in 2026. The companies winning unprompted LLM citations for startup-category queries are not necessarily the best-funded or most-PR'd — they are the ones whose entity records are internally consistent across Wellfound, Crunchbase, PitchBook, LinkedIn, and their own about pages. Six fields drive 80% of the citation outcome: one-liner, headcount, funding, founders, HQ city, and comp transparency. Lock the canonical version of each, push to all six surfaces, run a 90-day re-audit, and maintain a floor of active Wellfound job postings. The two-hour audit is the cheapest brand-authority compounding move available to operators this year.