Three companies grouped by where their demand is, not where their office is — which is the only grouping that means anything here. Sierra is San Francisco. Fin is Irish-founded and Ada is Canadian, and both belong on this page anyway, because 40% and 47% of their traffic is American and neither runs a European funnel. Between them they cover the full spread of the category: a $15.8B AI-native, a $3.6B exit, and a ten-year incumbent that got left behind.
| Sierra | Fin | Ada | |
|---|---|---|---|
| Founded | Early 2023 | 2011 | Jan 2016 |
| HQ | San Francisco | Dublin / SF | Toronto |
| US traffic share | 35.8% | 40.3% | 46.9% |
| European traffic | 6.0% | 3.7% | 2.9% |
| Segment | Fortune 50 | SMB→enterprise | Enterprise |
| ARR | $200M May 2026 | $400M total ~$100M is Fin | est. $60–110M never published |
| Raised | $1.585B | ~$241M equity | ~$200M nothing since 2021 |
| Valuation | $15.8B (May 2026) | $3.6B (acquisition) | $1.2B (2021, stale) |
| Team | ~600–1,000 | ~1,400 | ~421 |
| Customers | "hundreds" >40% of Fortune 50 | 12,000 on Fin 30,000 total base | 350+ flat since 2021 |
| Price | est. $180–350k yr 1 unpublished | $0.99/outcome published | ~$70k median ACV unpublished |
| Pricing model | Per resolution (Dec 2024) | Per outcome (2023, never moved) | Per resolution → back to volume |
| Risk reversal | Free when it escalates | $1M guarantee | none |
| Gross margin | not public | ~80% pre-AI | est. 60–70% |
| Traffic /mo | 288,731 | 501,889 | 253,026 |
| Paid share | 7.6% | 31.9% | 12.9% |
| Status | Scaling | Sold, Jun 2026 | Stalled |
Not nationality — demand. All three draw 36–47% of their traffic from the United States and 3–6% from Europe. Fin is Irish, Ada is Canadian, and neither has a European funnel: English-only sites, USD pricing, US enterprise sales. Being a European company is not the same as selling to Europe — which is exactly the test that separates this page from page 02.
Click to expand: founders, audience, journey, business model, growth, monetisation, the GTM playbook step by step, the moat claim and the honest counter-view.
Enterprise AI agents that act in back-end systems — refunds, plan changes, claims, mortgage applications — across chat, phone, SMS, WhatsApp, email and ChatGPT. Billed on resolution, not seats.
>50% of customers have >$1B revenue; 30%+ have >$10B; >40% of the Fortune 50. Targeting rule is a P&L number, not an industry: enterprises with $100M+ annual contact-centre spend, where calls cost $10–20 each.
Outcome-based. Taylor verbatim: "If the AI agent resolves the case, no human intervention, there's a pre-negotiated rate for that. If we do have to escalate to a person, that's free." No published pricing at all — sierra.ai/pricing is a live 404. Third parties reverse-engineer $1.00–2.50 per resolution and a ~$150k/yr platform floor; none of it confirmed.
It may be a services business in software clothing — Sierra builds the agents for customers, and Ghostwriter is arguably an admission it needs to automate its own delivery cost. ~79× ARR against public contact-centre comps at 1.8–2.5× and compressing. Gross margin is not public — the most important missing number about this company.
1. On 12 May 2026 Intercom renamed itself Fin. Fin is not a product
of Intercom any more — Intercom is the helpdesk product inside a company called Fin.
2. On 15 Jun 2026 Salesforce signed a definitive agreement to acquire Fin for
~$3.6B, expected to close Q4 FY2027. Both verified against the companies' own releases.
SMB + mid-market + enterprise, genuinely all three. Fin is the only credible player in the category with a true self-serve bottom of funnel: 14-day unlimited trial, 50-outcome minimum (~$49.50), buyable on a card. That is why it has 12,000 Fin customers where rivals have "hundreds". Enterprise ceiling: Fin API Platform at $250k+/yr.
$0.99 per outcome, unchanged since 2023 — through GPT-4 → Claude → Apex and a ~3× improvement in resolution rate. Holding the number is the price cut. $9.99 per qualified sales lead. Nothing charged for escalations or unanswerable queries.
But: a resolution is either "confirmed" (customer says thanks) or "assumed" — meaning no further help was requested. Customer silence is billed as success. A user who gives up is structurally indistinguishable from one who was helped. The refund-on-return clause only catches someone re-opening the same thread. Both the 76% headline resolution rate and the invoice rest on that definition.
Cannibalisation: they leaned in. A customer at 300 conversations/month who paid ~$100 in seats now generates ~$297. NRR 112%→146% is the proof. McCabe: "the only path to success in the future is through destroying your past."
Price is the most copyable thing in software — Zendesk restructured within months, Gorgias is at $0.90. Fin-for-Platforms makes Fin a feature on someone else's system of record, the weakest structural position in the stack. ~$300M of the $400M was still slow-growth legacy seat revenue at exit, valued at 2–3× against 27–30× for the Fin line. Selling at $3.6B rather than pressing on is itself the founders' verdict on whether the moat was enough.
The Fin Million Dollar Guarantee is the most aggressive GTM mechanic in this entire research, and we did not have it before. It runs in two forms, both published verbatim:
Read this next to the $0.99/outcome model and the "free when we escalate" term and you see the full ladder: Fin removed price risk, then performance risk, then existence-of-value risk. Each rung is only affordable because the previous one proved out — the same compounding logic as fonio's ad loop, applied to guarantees instead of cash.
The deck's competitive-landscape row for "Fin AI" reads 121 headcount, $20M revenue, 0.3M visits LTM. Its LinkedIn slide describes a feed "heavily anchored in academic research, open science, and domain-specific benchmarking, especially around multimodal financial LLMs" and an event called "a technology launch from the Fin AI Group."
That is not Intercom's Fin. It is
The Fin AI — a separate
financial-LLM research group (FinBen, FinMR, FinMTM; HuggingFace org TheFinAI), verified
directly. Intercom's Fin is fin.ai: ~1,400 employees, $400M total ARR,
~$100M on the Fin line, 3.0M visits in six months, and acquired by Salesforce for ~$3.6B in June
2026.
What to keep and what to drop. The profile slides (Million Dollar Guarantee, $0.99/resolution, 31.6M resolutions, the Decagon/Forethought bake-off, CX Score, Fin Tasks) are genuinely Intercom's Fin and are all usable. The headcount, revenue, traffic and LinkedIn-tone rows are measuring the wrong company and should be replaced. $20M for 2024 happens to be close to Fin's real 2024 trajectory ($1M → $12M ARR that year), so the revenue estimate survives by coincidence — but 121 people and 0.3M visits do not.
The deck lists Fin's limitations as "Intercom dependency; higher complexity; less SMB-oriented." Our read is close to the opposite on the third point: Fin is the only player in the category with a genuine self-serve floor — 14-day unlimited trial, a 50-outcome minimum (~$49.50), buyable on a card, 90% off for startups — which is why it has 12,000 Fin customers where Sierra and Ada have "hundreds". Both can be true at once: easy to start, hard to run well without support engineering. Worth settling before the deck goes anywhere, because it changes who the comparable is.
AI customer service on a proprietary "Reasoning Engine" over third-party frontier LLMs, 50+ languages. Founded eight years before the AI-native cohort — and losing to it anyway. This is the most instructive failure mode in the set.
The headline is "108% agentic AI ARR growth" — verbatim. That is a sub-line growing off a 2023 launch base, not total-company growth, and total-company growth was not disclosed. If it were comparable they would say so. 146% NRR is the meaningful figure: the installed base expands hard. And "350+ customers" has been cited unchanged from May 2021 to Aug 2026 — the logo count is flat-to-down over five years. All growth is expansion, none is acquisition.
Per-conversation → per resolved conversation (Oct 2023) → back to platform fee + prepaid conversation volume (2025–26). Their argument is sharp: outcome pricing "punishes success" — as the agent improves, the customer's bill rises. It is also commercially awkward, because it makes Ada the pricing outlier in the direction buyers read as vendor-favourable.
The LLM transition worked as a product exercise and failed as a market-share exercise. Ada spent 2022–23 shrinking 40% and rebuilding while the AI-native cohort was founded, funded and scaled straight past it. Sierra went $26M → $200M in 17 months; Ada, founded eight years earlier, likely sits below $100M with flat logos, no funding since 2021, and a website whose traffic (33-second visits, 46.6% referrals from design galleries and its own investor's site) is not acquiring anyone. Its "we complement, not replace, the agent desktop" position is precisely the position that gets absorbed by the platform it integrates with.
$2.03B raised across three companies. Sierra alone has raised $1.585B — roughly 200× the largest single round any company on the Europe page has ever taken (chatlyn's €8M). Sierra went $26M → $200M ARR in 17 months; Ada, founded eight years earlier, sits below $100M with a five-year-stale valuation and no raise since 2021.
The uncomfortable read for a European operator: Ada is what happens when you are early to the category but capital-constrained through the two years it gets decided in. It spent 2022–23 shrinking 40% and re-platforming from scripted flows to LLMs while the AI-native cohort was founded, funded and scaled straight past it. The product transition worked. The market-share transition did not.
Sierra charges nothing when the agent escalates to a human. Fin holds $0.99/outcome and adds a $1M guarantee. Ada tried per-resolution and publicly reversed, arguing it punishes success. Three coherent positions, one settling detail: Fin's "assumed resolution" bills customer silence as success — a user who gives up is structurally indistinguishable from one who was helped.
If we ever design outcome pricing, that definition is the whole thing, and it is the kind of mechanic that would fail a grey-mechanics review if it were pointed at consumers rather than at support tickets.
Fin sells SMB through enterprise and is the most paid-dependent in the entire research at 31.9% of traffic, including 11.6% display on msn.com, cnn.com and wsj.com — brand buying, not performance. Sierra sells to the Fortune 50 and barely uses paid at 7.6%. What separates them is not who they sell to but whether there is a self-serve floor a credit card can buy. Fin has one. Sierra and Ada do not.
Salesforce agreed to buy Fin for ~$3.6B in June 2026 — decomposing to roughly 2–3× on ~$300M of legacy seat revenue and 27–30× on the ~$100M Fin line. Read alongside NiCE buying Cognigy for ~$955M and Zendesk buying Ultimate.ai, the pattern is clear: if we enter this category we enter it after the pricing experiments and during the consolidation.
Sierra's channel is Bret Taylor's name — its top two non-branded organic search terms are literally
bret taylor and clay bavor. That is a former Salesforce co-CEO who chairs
OpenAI's board. It is not a channel you can decide to build. The replicable version is the
artefact, not the person: tau bench, the benchmark Sierra published and
open-sourced, pulls 3.60% of organic — nearly as much as the CEO's name.
Everything else here is enterprise field sales with a nine-month cycle. For a paid-acquisition business the useful material on this page is the pricing mechanics and the risk reversal — not the go-to-market. The transferable playbook is on page 01 and page 02.
SimilarWeb Pro, Feb 2026 – Jul 2026, worldwide, all traffic. Three separate reports, retrieved 26 August 2026. The equivalent European dataset is on page 02.
| Site | Total visits | Monthly | Unique/mo | MoM | Pages | Duration | Bounce | Desktop | Industry rank |
|---|---|---|---|---|---|---|---|---|---|
| fin.ai | 3.011M | 501,889 | 283,747 | +2.1% | 1.80 | 1:00 | 52.4% | 38.5% | Computers/Electronics #2,726 |
| sierra.ai | 1.732M | 288,731 | 145,699 | +33.7% | 2.76 | 1:45 | 43.5% | 57.5% | AI Chatbots & Tools #50 |
| ada.cx | 1.518M | 253,026 | 165,655 | −6.6% | 1.78 | 0:33 | 52.3% | 18.8% | Programming/Dev #4,971 |
Sierra is the only one of the three that SimilarWeb files in a category buyers would actually search — "AI Chatbots and Tools", where it ranks #50. Fin and Ada sit in the thousands of generic developer categories. That is a categorisation difference rather than a performance one, but it means Sierra is the only one appearing in the obvious comparison lists.
Ada's traffic quality is the weakest number on this page: 33-second average visits, 1.78 pages, 81% mobile, and 46.6% of traffic arriving via referral from design galleries (saaslandingpage.com 14.5%), trade press and its own investor's website (accel.com 6.0%). Read alongside 108% agentic-ARR growth and 146% NRR on a flat 350-logo count, it is consistent: Ada's growth is expansion inside existing accounts, and its website is not acquiring anyone.
| Site | #1 | #2 | #3 | #4 | #5 |
|---|---|---|---|---|---|
| fin.ai | US 40.3% +15% | India 6.7% +47% | UK 3.7% +13% | S. Korea 2.7% | Australia 2.2% |
| sierra.ai | US 35.8% +19% | India 9.1% +53% | UK 6.0% +38% | Canada 3.9% +43% | Singapore 3.4% +77% |
| ada.cx | US 46.9% +5% | Canada 5.7% +19% | Australia 3.0% +50% | UK 2.9% | Nigeria 2.1% |
Top paid non-branded search terms, July 2026. This is not category advertising. All three buy their rivals' product names — which means they are fighting over buyers who have already decided to purchase and are choosing a vendor. Expensive traffic, and the click is a coin flip.
Buys the entire competitive set by name
23% of Ada's entire paid budget goes
on the single word cognigy — the largest single conquest term anywhere in eleven
reports. Note it also buys the other two companies on this page.
Rivals plus voice infrastructure
The only one of the three buying
infrastructure alongside rivals — retell ai and 11labs are the same
build-it-yourself intent fonio targets, though at a much smaller share of budget.
Two names, plus Japan and Korea
Highly concentrated: two names take 34% of the budget. The Korean and Japanese terms are the localisation push showing up in the ad account.
All three buy rival product names. On
page 02, fonio buys twilio, vapi and
retell — developer infrastructure — and Trengo buys whatsapp api.
The difference is what the competing offer is. Against a rival product you are one of several vendors. Against "build it yourself on Twilio" the alternative is six engineer-months. Cheaper traffic, weaker competition, higher intent — and nobody on this page is doing it at scale.
| Site | What people actually search |
|---|---|
| sierra.ai | bret taylor 5.41% (+69%) · clay bavor 3.70% (+236%) ·
tau bench 3.60% · takeoff ai 3.40% · シエラ ソフトバンク 2.80%
The top two non-branded organic terms are the founders' names. Third is the benchmark they published and open-sourced. This is founder publicity working as a measurable acquisition channel — and tau bench at 3.60% shows the artefact pulls nearly as much as the CEO's name, which is the replicable half. |
| fin.ai | intercom academy 5.71% · ai solution customer supp… 5.08% ·
intercom jobs 3.34% · intercom 2.92% · blueprint intercdom 1.67%
Four of five are the old brand. Fifteen years of Intercom equity still doing the work three months after the company renamed itself Fin — which is exactly the "baggage" the rebrand was meant to shed. |
| ada.cx | ada cx jobs 13.27% · ada chat casino 10.20% ·
alucinaciones de la ia ejem… 10.20% · website importer 8.16% ·
how many cs tickets does … 7.14%
None of these is a buyer. Job-seekers, a name collision with online casinos, and a Spanish-language query about AI hallucinations. Ada's organic channel is not producing demand. |
The only creative-level evidence in the research: real captured ads with the copy transcribed. Fin runs a different job on each platform and never repeats a message.
Two paid video testimonials, identical copy: "Leading AI company Anthropic wanted an AI agent to power exceptional customer service experiences. See why they chose Fin."
No product claim at all. The whole ad is brand association — if the frontier AI lab picked us, you don't need to evaluate our AI. Organically the showcase page is the opposite: technical, research-led, with the promotional lift coming from partner accounts. An OpenAI repost of Fin's AI Engine diagram pulled 776 reactions and 93 reposts.
40K followers and the last organic post was 23 April 2024. The paid side is the sharpest copy in the research:
"Fin AI Agent instantly resolves 51% of your support tickets, emails, and messages on Zendesk. Set it up in less than an hour — no migration required." · "99¢/resolution — no seats and no minimum spend."
Three objections killed in two lines: a specific number instead of "up to"; the rival's platform named so there is nothing to migrate; and a price with the two scariest words in SaaS explicitly removed — seats and minimum.
Three structured playlists: hero explainers, the Pioneer summit cut into episodes, and a "Built For You" feature series. Leaders on camera paired with product UI in almost every video.
The tension worth naming: YouTube is 63.8% of Fin's social traffic, yet individual videos sit at 150–8,500 views. Small numbers doing real work — this is a sales-enablement and evaluation library, not a reach channel.
Fin runs its own r/fin_ai_agent — ~600+ members,
weekly posts, engineering-first tone, deep technical write-ups on infra migrations and latency.
Engagement is modest (≈5–12 upvotes) and concentrated on architecture threads.
Compare Sendbird, which has no owned community and whose Reddit presence is other people's comparison threads, where the recurring objections are pricing, vendor lock-in, and total cost versus "roll your own" — the same intent fonio buys on paid search.
Twenty-one buyer-intent queries were tested. Almost none contain a brand name and almost all are integration questions.
1. The category's demand is expressed as an integration problem, not a product search. Buyers type "connect AI to my helpdesk", not "best AI support agent". That is why Fin's entire paid message is "on Zendesk, no migration required", and why Ada's "we complement the agent desktop" positioning made sense right up until it made Ada absorbable.
2. Roughly a third of the queries are people intending to build it
themselves. That is the same intent pool fonio buys with twilio and
vapi, arriving through a different door — which confirms the flank is real and sizeable
rather than a quirk of one ad account.
Who shows up: Fin appeared most often (5 times, frequently ranked #1 in paid), Sendbird twice. Also surfacing: Ada, Zendesk, Front, Cohere, involve.me, Noupe, Fyxer.ai, Moxo — a wider and messier competitive set than any single vendor's comparison page admits.
How to treat these numbers. SimilarWeb Pro is panel-and-model-based estimation, not measured analytics. Levels can be materially wrong; rankings and ratios between sites in the same dataset are far more reliable than absolute values, and channel shares are more reliable than channel volumes. Every conclusion here is drawn from a comparison, not from a level.