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Product analytics with an AI analyst · USA

Databuddy: Product, team and how it was built

Solo founderFundedB2BAnalytics

Databuddy (Product analytics with an AI analyst, USA): Solo founder in YC Fall 2026 with paid plans live, November 2026. Evidence grade E: no revenue figure was checked. Team: 1 founder; Y Combinator lists a team size of 1 in November 2026. Launched 2025; still running.Added 5 November 2026

Outcome
Solo founder in YC Fall 2026 with paid plans live, November 2026
Evidence
E no revenue figure was checked
Launch
2025
Status
Still running
Team
1 founder; Y Combinator lists a team size of 1 in November 2026
Outside funding
Y Combinator, Fall 2026 batch (amount not stated in the sources)
Group
Documents, data and slides
Main channel
Not stated
No revenue figure

What is not verified

No revenue figure was found. This page looked for a TrustMRR or other payment-processor profile, a founder interview with figures and a filing, and found none. The traction claims (#5 Product of the Day on Product Hunt, more than 800,000 views of an X post) are the founder's own, from the launch post of 5 November 2026; the Product Hunt product page answered 404 and X needs a login. The home page shows "Used by developers at" OpenAI, Vercel, Supabase, Upstash and CodeRabbit with no source for the claim. One quoted customer is described as "Context.dev" in the launch post and as "Founder, Rentmyheader" on the home page, and context.dev also appears in the data policy as a supplier for AI investigations. A reader could look for a revenue figure in a later Y Combinator Demo Day post or a payment-processor profile. This story is grade E: the business is real and its product, price and customers are described from public pages, but no revenue figure was checked. Aiolum shows it as an idea worth studying, not as proof that it makes money.

Databuddy is product analytics, software that records what visitors and users do on a website or app (page views, sign-ups, clicks, purchases) and turns it into charts. Its tracker is cookieless: it does not store a cookie, a small file that identifies the browser, and the company says it avoids fingerprinting by default. The AI analyst, Databunny, turns a plain question into SQL, the language used to query a database, runs it, and shows the query next to the answer. Developers can also reach the data through an MCP server, a standard interface that lets AI coding agents such as Claude Code or Cursor call a service's tools.

Issa Nassar founded it alone. In the Y Combinator launch post of 5 November 2026 he writes that he started building it in Palestine and now builds it full time in the Fall 2026 batch. Y Combinator lists the company with a founding year of 2025, a team size of 1, San Francisco as its location, and the one-line description "AI Data Analyst for fast-growing teams".

No revenue figure was found. The pricing page lists a free plan up to 10,000 events a month and paid plans from US$9.99 to US$799 a month; the founder's traction claims are a Product Hunt ranking and views of an X post, which this page could not check.

Databuddy: Solo founder in YC Fall 2026 with paid plans live, November 2026. Product analytics with an AI analyst, USA, solo founder, evidence grade E.
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01

How much revenue does Databuddy make?

Each row shows the evidence grade and the source numbers from the list at the end of this page. The grades are explained in How Aiolum verifies.

A one-person company in Y Combinator's Fall 2026 batch with five public paid plans and no published revenue figure
FactValueGradeHow we knowSources
Revenuenot publishedENo payment-processor profile, founder figure or filing was found. The launch post gives no revenue.[2]
Founder and teamIssa Nassar, solo founder; team size 1CLaunch post: "I'm a solo founder." Y Combinator's company page lists team_size 1 and one founder.[1, 2]
Founded2025CY Combinator company page, year_founded 2025. The month is not stated in any source read.[1]
AcceleratorY Combinator, Fall 2026CY Combinator company page and launch post, 5 November 2026. The investment amount is not stated in the sources read.[1, 2]
LocationSan Francisco; building started in PalestineCY Combinator lists San Francisco, US. Launch post: "I started building Databuddy in Palestine".[1, 2]
How Y Combinator describes it"AI Data Analyst for fast-growing teams"CThe one-line description on the Y Combinator company page. The pricing page title is "Pricing: an AI analyst for your product".[1, 4]
Cheapest paid planUS$9.99 a monthCPricing page and the public pricing endpoint, read 5 November 2026. Free up to 10,000 events a month.[4]
Plans with AI investigationsUS$299 and US$799 a monthCBusiness and Scale, with 100 and 250 scheduled AI investigations a month. The pricing page compares them with a data analyst at "around $8,000 a month", its own estimate.[4]
Traction claimed in the launch post#5 Product of the Day on Product Hunt; Y Combinator announcement on X "passed 800K views"CFounder's claims, 5 November 2026. The Product Hunt product page answered 404 and X needs a login, so neither was checked.[2]
AI model named by the companyClaude Sonnet, for AI insightsCChangelog entry of May 2026: a length limit was widened to match "what Claude-Sonnet routinely writes". The data policy says AI requests go through Vercel's AI Gateway and "The provider depends on the configured model."[7, 8]
Privacy designno cookies, no fingerprinting by defaultCAbout page: "Databuddy avoids cookies and fingerprinting by default". The FAQ adds that the tracker uses browser storage and that "Cookieless does not automatically mean consent-free."[3, 6]
Self-hostingnot offeredCHome page FAQ: "Can I self-host Databuddy? No." The GitHub organization lists side projects; no main Databuddy repository was public on 5 November 2026 (the path answered 404).[3, 9]
Time from founding year to the launch postabout 16 monthscalcCalculated: from mid-2025, the middle of the founding year, to November 2026. The true value lies between 11 and 22 months.[1, 2]

How to read this table: a grade C value is a statement by the company or its founder, on its own pages or its Y Combinator pages. A "calc" value was computed on this page. No value is grade A or B, and no revenue figure exists.

Databuddy prices on 5 November 2026, from its pricing page and its public pricing endpoint (grade C)
PlanPer month, billed yearly (US$)Per month, billed monthly (US$)Limit
Free010,000 events a month, 10 AI credits
Hobby9.9930,000 events, 20 AI credits plus 1 a day
Pro49.991 million events, 350 AI credits plus 5 a day
Business2992 million events, 100 investigations, 1,500 AI credits
Scale7996 million events, 250 investigations, 3,000 AI credits, SSO
Enterprisecustomcustom volume, security review, SLA

All plans are billed monthly; the pricing FAQ says there is no annual billing. Events above the allowance cost US$0.035 per 1,000 on Hobby and Pro, with lower rates at higher volumes. Business and Scale are called early-user prices, locked while the customer keeps the plan, and extra investigations cost US$1 each. Free stops collecting events at 10,000 a month.

02

When did Databuddy launch, and how did it grow?

From a solo project started in Palestine to a Y Combinator launch, as the company's own pages date it. Each entry carries its grade.

  1. 2025CIssa Nassar starts building Databuddy alone in Palestine. Y Combinator lists 2025 as the founding year. [1, 2]
  2. April 2026CThe changelog records a bot-signature database of more than 970 crawlers and cost controls for the AI agent. [7]
  3. May 2026CA changelog entry on AI insights names Claude Sonnet as the model whose summaries the limits were sized for. [7]
  4. October 2026CWeekly changelog entries continue, with most entries signed by the founder's handle. [7]
  5. 5 November 2026CLaunch post on Y Combinator for the Fall 2026 batch: free up to 10,000 events a month, then from US$9.99, as the post states. [2]
03

Why did Databuddy work?

Four causes, in the order they mattered. Each one is a reusable lesson.

01

An AI analyst that shows its query

Databunny answers a plain question, then shows the SQL it ran, so a founder can check the number instead of trusting it. The FAQ calls this the answer to "Can I trust the AI answers?"

02

One script for several tools

Traffic, events, funnels, errors, Web Vitals, feature flags and revenue come from one install. The launch post lists Google Analytics, PostHog or Mixpanel, Sentry and Stripe as the separate tools it replaces.

03

Priced on the AI work, not only on events

The low plans sell analytics with a few AI credits. The pricing page sells the two top plans as scheduled AI investigations that post findings to Slack, and compares them with the cost of a hired analyst.

04

Built for coding agents

An MCP server, an llms.txt file and an OpenAPI description let agents such as Claude Code or Cursor read the analytics and create funnels or goals from the editor.

How it was built

These details come from the company's changelog and data policy. They are grade C. [7, 8]

  • Analytics events and revenue are stored in ClickHouse, a column database built for fast counts over many rows; webhook receipts are kept in PostgreSQL.
  • Hosting is split across Hetzner, Unkey, Vercel, Bunny.net for the tracker files, Cloudflare at the network edge and PlanetScale for account data.
  • AI requests go through Vercel's AI Gateway to the configured model provider; the changelog names Claude Sonnet for AI insights.
  • Stripe takes payments and Autumn handles subscriptions, entitlements and metered usage; Resend sends email.
  • The changelog is published weekly, and most entries name the founder's handle as author.

Tools named in the sources

Each one opens its page in the Tools tab, with every story that uses it.

Anthropic APICDrizzle ORMCNext.jsBVercelCClickHouseCPostgreSQLCHetznerCUnkeyCbunny.netCCloudflareCPlanetScaleCContext.devCMicrolinkCStripeCAutumnCDubCProduct HuntCXCResendCDiscordCThe Context CompanyCAxiomCSuperlogCOpenAIC
04

Who tried this before Databuddy, and why did they fail?

Three companies in our database of failed startups promised analytics insights to teams without a data team, or predictions from product data. The values below are from that database and are not independently verified.

Died 2011 to 2019Burned US$15M

SumAll

The promise

Marketing and sales data from many platforms in one dashboard for small businesses without a large team.

Why it died

It could not stand apart from Google Analytics, Tableau and free tools, and its price did not match the value small businesses saw.

Competition
Died 2012 to 2018Burned US$4.7M

Preact

The promise

Predict which SaaS customers would churn from their product usage.

Why it died

Larger customer-success platforms offered similar predictions inside a fuller product.

Competition
Died 2021 to 2024Burned US$15M

Toplyne

The promise

Use product data and AI to find which free users would pay.

Why it died

Budgets were cut after 2022, and the gain from better lead scoring was hard to prove.

No Market Need

The failed startups come from our database of 1,749 dead startups, retold here in our own words. Its entries are AI-assisted summaries of public sources, so these cards carry no evidence grade.

What changed

SumAll and Preact sold insight from data to teams that had no analyst, and both lost to larger tools that offered the same charts or predictions. Toplyne added AI predictions on top of existing analytics and could not prove the return. Databuddy is the same promise: answers without a data team.

Two things differ. A language model can now write the query for any question, not only for the reports a vendor designed, and Databuddy shows that query so the answer can be checked. And one founder with managed services (ClickHouse, Vercel, Stripe, Autumn) can run the whole stack, so the company does not need the funding the three predecessors raised before it finds out whether people pay.

05

Can one person copy Databuddy now?

The product, hard. The idea, yes.

Analytics is a crowded field with large, funded players, and Databuddy combines many features that took one founder over a year to build. The narrower idea can be copied: put an AI analyst that shows its work on top of data a customer already has.

Where it is still open: AI analysts for one data source each: Stripe revenue, app-store reviews, ad spend, support queues, or open-source package downloads.

  1. 1Pick one data source that small teams already collect but do not read (payments, support tickets, ad accounts).
  2. 2Let a model write the query, and always show the query next to the answer.
  3. 3Sell scheduled checks that post only real changes to the team's chat, priced against the cost of a hired analyst.
  4. 4Offer an MCP server so coding agents can read and change the setup.

What could go wrong for Databuddy?

The risks are the mirror image of the causes above.

What is not verified

No revenue figure was found. This page looked for a TrustMRR or other payment-processor profile, a founder interview with figures and a filing, and found none. The traction claims (#5 Product of the Day on Product Hunt, more than 800,000 views of an X post) are the founder's own, from the launch post of 5 November 2026; the Product Hunt product page answered 404 and X needs a login. The home page shows "Used by developers at" OpenAI, Vercel, Supabase, Upstash and CodeRabbit with no source for the claim. One quoted customer is described as "Context.dev" in the launch post and as "Founder, Rentmyheader" on the home page, and context.dev also appears in the data policy as a supplier for AI investigations. A reader could look for a revenue figure in a later Y Combinator Demo Day post or a payment-processor profile.

Competition from large analytics tools

Databuddy names its competitors itself: its home page has comparison pages for Google Analytics, PostHog, Plausible, Mixpanel and Umami, and the launch post invites users who are "Switching from Google Analytics, PostHog or Plausible". Those products are older and larger, and the larger ones can add an AI analyst of their own. This page did not read their pricing.

Dependence on model providers

The AI analyst runs on outside models. The data policy says AI requests go through Vercel's AI Gateway and that "The provider depends on the configured model", and the changelog names Claude Sonnet. Model prices or limits set by the provider change the cost of every AI credit and investigation the plans include.

Privacy claims and their limits

The company says it avoids cookies and fingerprinting by default, and its own FAQ adds that the tracker uses browser storage and that cookieless does not mean consent-free. Whether a site needs a consent banner depends on its own setup and local law.

More in Documents, data and slides

Other businesses in the same group, best evidence first. All 46 stories in the group, 14 with grade-A revenue.

AI presentation generator and Google Slides add-on · India

MagicSlides

Evidence A
$723K total, now $9K/mo

Team of 2 to 10 · 45 months after launch, revenue falling

Said US$19K a monthRecords US$9.6K in JulyDid not hold

It appeared in January 2023 inside Google Slides, a program where people already work, when writing slides from one sentence was new, and users showed it to each other without paid advertising. A blog about presentation topics then brought about 80% of new users from Google search, by the founder's account. Both channels weakened: search traffic fell, and Google added the same function to Slides. The verified total is real, and so is the fall: monthly revenue fell by half between February and July 2026.

7 grade-A facts · 4 that failed before it
AI presentation generator (web app) · USA

GenPPT

Evidence A
$110.6K in 12 months

Solo founder · 29 months after launch, revenue falling

It is run by a search marketer: its pages target what people type into Google, and its best month came from a list article on another company's blog that ranked there. A US$1 trial that needs a card turns visitors directly into subscribers at US$25 a month or US$99 a year.

7 grade-A facts · 3 that failed before it
Step-by-step guides and interactive walkthroughs from screen captures, with AI writing, voiceover and translation · India

Guidejar

Evidence A
$85.1K in 12 months

Solo founder · 36 months after launch, revenue flat

The first customers came from a lifetime-deal sale on AppSumo, at a time when the product had no AI at all. That gave about a thousand users, word of mouth and a Powered by Guidejar link on every free guide. From April 2024 the founder sold subscriptions instead, and added AI writing, voiceover and translation to the paid plans, metered in credits.

5 grade-A facts · 4 that failed before it
AI presentation generator · United Kingdom

Presentia AI

Evidence A
$60K total, now $1.1K MRR

Team of 2 to 10 · 24 months after launch, revenue falling

It sold a simple promise, a finished PowerPoint file from one sentence, at a low price: in 2024 and the first half of 2025 the archived pricing showed unlimited decks for US$9.99 a month. Stripe payments read by TrustMRR add up to US$60,120 since the start. The verified monthly figures also show a steady fall after November 2025, when the plans had moved from unlimited use to slide credits, and the founder put the business up for sale.

9 grade-A facts · 4 that failed before it
AI functions for Google Sheets (add-on) · India

SheetAI

Evidence A
$52K total, now $367 MRR

Team of 2 to 10 · 47 months after launch, revenue falling

It put a language model inside Google Sheets from November 2022, and Google's marketplace brought more than 201,000 installs. Few installs paid: US$52,136 of verified revenue in 47 months is about US$0.26 per install. Its most important result may be indirect: a request for a pitch deck for SheetAI led the founder to build MagicSlides, which by its own verified data earned about 14 times as much. SheetAI's own revenue is now falling, and Google has offered a similar AI function inside Sheets since June 2025.

5 grade-A facts · 4 that failed before it
AI agent inside Excel · France

ElyxAI

Evidence A
$2.8K MRR, listed for sale

Solo founder · 15 months after launch, revenue falling

It does the work in the cells instead of explaining what to paste, and it works in the Excel that people already have, without a Microsoft Copilot license. The founder already taught Excel to a large French audience. The AI models are bought by the request from OpenAI and Anthropic, so one person could build and run it.

9 grade-A facts · 5 that failed before it

Built with the same tools

Businesses whose sources name tools that Databuddy also uses: Stripe, Autumn, Anthropic API, Vercel. Every tool has its own page in Tools.

Branching AI chat on a desktop canvas · USA

Slashspace

Evidence A
$131K total revenue

Solo founder · 25 months after launch, revenue falling

A normal chat window is one long thread, and a side question either breaks that thread or is never asked. The founder sold a fix for that one problem to heavy AI users. The subscription version earned little; the one-time licence that followed sold to many buyers, and Stripe data on TrustMRR shows US$131,070 in total. Sales then fell, because each one-time buyer pays only once.

7 grade-A facts · 4 that failed before it
Open-source social media scheduler for people and AI agents · Israel, company registered in Hong Kong

Postiz

Evidence A
$3.2M/yr run rate

Solo founder · 27 months after launch, revenue growing

Said US$245K a monthRecords US$263K MRRSaid less than the records

The founder took a twenty-year-old product category with no open-source entry and open-sourced all of it, which gave him millions of Docker downloads and 37,000 GitHub stars without a marketing budget. Revenue stayed small for a year. It multiplied when he turned the product toward people who automate their posting with n8n workflows and, from late 2025, with AI agents, which need an API-first scheduler and keep paying because they post without human effort.

6 grade-A facts · 5 that failed before it
AI designer for mobile app screens · USA

Sleek

Evidence A
$247K/yr run rate

Team of 2 to 10 · 11 months after launch, revenue falling

It took a narrower job than the general AI design tools, mobile apps only, for people who build apps without design skills. The three founders reused what they had learned from four earlier design tools, built it in three weeks, and showed finished designs on X before the launch. Each new Gemini model gave them a better result and a new demo to post.

5 grade-A facts · 4 that failed before it
AI app builder · Germany, now USA

Softgen

Evidence C
Sold at $500K ARR

Team of 2 to 10 · sold 8 months after launch

A technical founder released an early full-stack AI app builder in July 2024, and revenue stayed flat for four months. Then a second person joined who worked only on distribution, and annual recurring revenue grew about 25 times in four months. They sold the product while the growth was visible and kept their company for the next product.

Every number graded · 5 that failed before it

Sources

The grade next to each source is the best grade that the source can support. "Read in full" means that the text of the page was downloaded and the numbers were checked in it.

  1. C Y Combinator company page: Databuddy
    Read in full, 5 November 2026 (the page's embedded data). Source for the one-line description, founding year, team size, location, batch and founder.
  2. C Y Combinator launch post, 5 November 2026: Databuddy: Product analytics for founders without a data team
    Read in full. Founder's post. Source for the problem statement, the solo-founder statement, the start in Palestine, the traction claims and the price summary.
  3. C Databuddy home page
    Read in full, 5 November 2026, including the FAQ answers in the page data. Source for the features, the self-hosting answer, the cookie answer and the customer quotes.
  4. C Databuddy pricing page and public pricing endpoint
    Read in full, 5 November 2026, with https://www.databuddy.cc/api/pricing (allowed by robots.txt) for the exact allowances and overage rates.
  5. C Databuddy: Databunny, the AI analyst
    Read in full. Source for how chat and scheduled investigations work.
  6. C Databuddy: About
    Read in full. Source for the cookie and fingerprinting statement and the agent interfaces.
  7. C Databuddy changelog
    Read the entries from March to October 2026 shown on the page. Source for the model name, the bot database and the authorship of entries.
  8. C Databuddy data policy
    Read in full. Source for the storage, hosting, billing and AI providers.
  9. C GitHub organization: databuddy-analytics
    Read the repository list, 5 November 2026. The path /databuddy-analytics/Databuddy answered 404.
  10. C Database of failed startups, local export
    Local export. AI-written summaries, not independently verified. Source for the failed predecessors.

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