# Lark

Aiolum story: https://aiolum.com/story/lark/ · added 2026-11-06 · updated 2026-11-06

**In short.** Lark (AI agents for purchasing, inventory and sales work at wholesale distributors, United States): Live with a published customer story, November 2026. Evidence grade E: no revenue figure was checked. Team: 2 co-founders; Y Combinator lists a team size of 2 in November 2026. Launched September 2026; still running.

AI agents for purchasing, inventory and sales work at wholesale distributors · United States · AI-native · team of 2 to 10 · still running · group: Operations, logistics and trades

- Outcome: Live with a published customer story, November 2026 (evidence grade of the headline number: E; no revenue figure)
- Launch: September 2026; months from launch to the outcome: 2
- Team: 2 co-founders; Y Combinator lists a team size of 2 in November 2026
- Outside funding: Y Combinator, Fall 2026 batch; amount not published
- Main factor: Vertical focus
- Meters, 1 to 4: evidence strength 1, copyable pattern 2, capital needed 2
- Tags: AI-native, Small team, Funded, Running, B2B, Wholesale distribution

Links:

- Visit larkagents.com: https://larkagents.com/

**The product.** Software agents that connect to a distributor's existing ERP, email, documents and CRM. They rank what to reorder, draft purchase orders and vendor emails, forecast demand per item, flag stock problems, enter customer orders and draft replies to quote requests. Actions in the ERP run only inside workflows and limits that the customer approves.

**Why it worked.** Distributors of plumbing, electrical and hardware goods keep tens of thousands of items in old ERP systems and do much of the reorder and quote work by hand. Lark sells agents that sit on top of the ERP instead of replacing it, so the customer does not have to migrate. The one published customer, Interline Hardware, says the reorder list now takes about 30 minutes a day instead of three hours.

Evidence grades: A = disclosed by a public company, a filing or a payment processor, or verified by one; B = two or more independent reports agree, or a journalist confirmed it; C = a founder claim that no one else verified; D = reported, not verified: one founder claim or a third-party estimate with no second source; E = no revenue figure found, so the headline is a non-money fact and the other facts carry their own grades; calc = computed on this page from graded facts.

## Summary

Lark sells AI agents, programs that use a large language model to read data, decide on a next step and take an action, to wholesale distributors. The agents connect to the customer's ERP (enterprise resource planning system, the database where a distributor keeps items, stock, orders and prices), such as Epicor Prophet 21, Infor CSD or NetSuite. They draft purchase orders (POs, the orders a distributor sends to its vendors), forecast demand, flag stock problems, enter customer orders and draft quote replies.

Jason Wang and Michael Wang founded the company in San Francisco in 2026 as LarkAI Technologies, Inc., and Y Combinator lists it in the Fall 2026 batch with a team of 2. The site's terms are dated 16 September 2026, and the Internet Archive first saved the site on 29 September 2026. The company publishes one customer story: Interline Hardware, a hardware wholesaler with more than 60,000 items.

No revenue figure was found, so this story has grade E. The site publishes no prices; customers start with a pilot after a call.

## Pricing

Lark prices read on 6 November 2026 from the company's site (grade C): no list price is published

| Plan | Per month, billed yearly (US$) | Per month, billed monthly (US$) | Limit |
|---|---|---|---|
| Pilot after a booked call | no list price |  | setup of one to two months; more agents can be turned on later |

Every page offers "Book a meeting" for a 30-minute call. The FAQ says most setups take one to two months and start with a pilot in which Lark and the customer's team map data, items, vendors and rules. No plan names, prices or limits appear on any page that was read, and the site has no pricing page.

## How much revenue does Lark make? The numbers, graded

A two-founder Y Combinator company with six agents, one named customer and no published revenue or prices

| Fact | Value | Grade | Note | Sources |
|---|---|---|---|---|
| Founded | 2026, San Francisco | C | Y Combinator company page, read 6 November 2026. | [3] |
| Team | 2 people: Jason Wang (CEO) and Michael Wang (co-founder) | C | Y Combinator company page lists team size 2 and both founders. | [3] |
| Funding | Y Combinator, Fall 2026 batch | C | Y Combinator company page; the home page says "Backed by Y Combinator". No amount is published. | [1, 3] |
| Earliest public date of the site | terms last updated 16 September 2026; first archive capture 29 September 2026 | C | Terms of service page and the Internet Archive capture index. | [5, 6] |
| Agents offered | Purchasing, Demand forecasting, Inventory monitoring, Order entry, Sales operations, Data analysis | C | Home page and FAQ. The FAQ adds that the company can also build customized agents. | [1, 4] |
| ERPs named | Epicor Prophet 21 and Eclipse, Infor CSD, Oracle NetSuite, Acumatica, SAP Business One, Microsoft Dynamics 365 Business Central, Sage 100/300, Spire, DDI System Inform | C | FAQ, which says this is not a complete list. It also names Outlook, Gmail, Google Drive, SharePoint, OneDrive, Dropbox, QuickBooks and HubSpot. | [4] |
| Control over ERP changes | only through approved workflows with limits | C | FAQ example: "POs under $5,000 for approved vendors go through on their own; bigger ones wait for a buyer." Every read and action is logged. | [4] |
| Named customer | Interline Hardware, more than 60,000 inventory items | C | Company's customer story. The customer's head of purchasing is quoted by first name only. | [2] |
| Customer's time saved | about 60 hours a month | C | Customer quote in the company's story: the reorder list took three hours a day and now takes about 30 minutes. A customer outcome, not Lark revenue. | [2] |
| Setup time | one to two months for most setups; under one month for Interline | C | FAQ and customer story. | [2, 4] |
| Hosting | Google Cloud in the US | C | FAQ. Customer data is not used to train models, the FAQ says. | [4] |
| Time from launch to the customer story | about 2 months | calc | Calculated: September 2026 to November 2026. | [2, 5] |

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

## When did Lark launch, and how did it grow? Timeline

From incorporation to a published customer story in about two months. Each entry carries its grade.

- **2026** (grade C [3, 5]): Jason Wang and Michael Wang found LarkAI Technologies, Inc., a Delaware corporation, in San Francisco.
- **16 September 2026** (grade C [5]): The terms of service are last updated; the privacy policy takes effect on 17 September.
- **29 September 2026** (grade C [6]): The Internet Archive saves larkagents.com for the first time.
- **Fall 2026** (grade C [3]): Lark is in the Y Combinator Fall 2026 batch.
- **November 2026** (grade C [1, 2]): The site offers six agents and publishes a customer story about Interline Hardware.

## Why did Lark work?

### One industry, one set of systems

Lark sells only to distributors, and its demos use their words: backorders, reorder points, vendor lead time, price lists per customer. The FAQ names more than ten ERPs that distributors use. A narrow buyer lets a two-person team write agents that know the data layout of those systems.

### On top of the ERP, not instead of it

Replacing an ERP is a project of years for a distributor. Lark reads and writes the existing ERP, so the buyer's only change is a pilot of one to two months.

### Approval limits as the safety rule

The customer approves each workflow once with limits, for example automatic POs below US$5,000 for approved vendors, and Lark logs every action. This answers the main fear about agents that change business records.

## How it was built

These details come from the company's own pages. They are grade C.

- Hosted on Google Cloud in the US; data encrypted in transit and at rest; credentials kept in a separate vault per customer that does not reach the AI model.
- The terms say AI features use "third-party AI models"; no model provider is named.
- The web app uses PostHog for analytics and session replay, according to the privacy policy.
- Setup is done by the Lark team with the customer during a pilot.

Sources: [4, 5]

## Who tried this before Lark, and why did they fail?

Three companies in our database of failed startups tried to digitize distribution or small-business inventory work and failed. The values below are from that database and are not independently verified.

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

### ShopX (2015 to 2022; funding US$60M; cause: Unit Economics)

- Promise: Digitize India's corner shops and cut out distributor middlemen.
- Why it died: The distributors who controlled supply did not give way, and customer acquisition cost more than customers brought in.
- Record: 

### Kyte (B2B SaaS) (2020 to 2024; funding US$10M; cause: Unit Economics)

- Promise: One platform for inventory, billing and CRM for small businesses in India.
- Why it died: Low revenue per customer, high acquisition cost and long sales cycles.
- Record: 

### Zilingo (2015 to 2022; funding US$340M; cause: Ran Out of Cash)

- Promise: Supply-chain software, financing and inventory tools for fashion merchants and factories.
- Why it died: It spent far more than it earned, and an accounting scandal ended investor trust.
- Record: 

## What changed

The predecessors tried to replace how distribution works, or to sell a new all-in-one system to many small buyers. Lark sells to distributors that already have an ERP and adds agents on top, so it does not fight the distributors or ask them to migrate.

Language models can now read customer emails, purchase orders in PDF files and messy ERP records, which made order entry and quote replies automatable without custom rules per customer. Whether this sells at a price that covers the one-to-two-month setup is not yet shown by any public figure.

## Can one person copy Lark now?

**Verdict: Yes, for someone who knows one industry's systems.**

The method is a narrow buyer, agents on top of the systems that buyer already uses, and approval limits. A solo founder can copy it, but setup by hand with each customer limits how many customers one person can serve.

1. Pick an industry that runs on a few old ERPs, and learn their data.
2. Automate one daily task that the buyer can measure in hours, such as the reorder list.
3. Let the customer set limits for automatic actions, and log every action.
4. Publish a named customer story with the time saved.

**What is still open.** Other trade industries on old ERPs: food service distribution, building materials, auto parts, medical supply.

## What could go wrong for Lark?

- **What is not verified.** No revenue figure for Lark was found. We looked for a payment-processor profile, a founder interview with figures, a Y Combinator launch post and a filing. The customer story gives a customer outcome (about 60 hours a month saved), which is not Lark revenue. Jason Wang's Y Combinator profile says that his previous company, Datost, also backed by Y Combinator, "grew ARR to 400k in 8 weeks"; that is his own statement about a different company and was not checked. A reader could look for a launch post, a funding announcement or an interview with the founders.
- **Trust signals.** The only testimonial is quoted as "Mike, Head of Purchasing, Interline Hardware", with a first name only. The customer company is named. The Y Combinator backing is confirmed by the Y Combinator company page.
- **Setup by the company.** The site says "We handle the setup with your team", and the FAQ says "We can also build customized agents for your workflows". The product is software, but each customer needs a pilot of one to two months set up by the Lark team.
- **Website tracking.** The privacy policy says the website uses "third-party visitor identification that may associate activity with a company" and Google Ads measurement, and that the app's session replays can include customer business records.
- **Competition and model providers.** LineSight, another story on this site, sells AI order entry to metal service centers, and FastQuery an AI assistant to hardware stores. Lark's terms say it uses "third-party AI models" without naming them, so its dependence on one provider cannot be judged.

## Sources

1. Lark home page: Specialized AI Agents for Distributors — https://larkagents.com/ (grade C). Read in full on 6 November 2026. Source for the agents, the approval limits and the Y Combinator backing.
2. Lark customer story: How Interline Hardware manages inventory and purchasing with Lark — https://larkagents.com/customers/interline-hardware (grade C). Read in full. Source for the named customer, the item count, the setup time and the time saved.
3. Y Combinator company page: Lark, AI agents that automate workflows for distributors — https://www.ycombinator.com/companies/lark-2 (grade C). Read the company data embedded in the page: year founded, team size, batch, location and founder profiles.
4. Lark FAQ — https://larkagents.com/faq (grade C). Read in full. Source for setup time, the ERPs named, the control rules and the hosting.
5. Lark Terms of Service, last updated 16 September 2026, and Privacy Policy, effective 17 September 2026 — https://larkagents.com/terms (grade C). Read both in full (the privacy policy is at https://larkagents.com/privacy). Source for the legal entity, the third-party AI models, PostHog and the tracking.
6. Internet Archive capture index for larkagents.com — http://web.archive.org/cdx/search/cdx?url=larkagents.com (grade C). Read the capture list. The first capture is dated 29 September 2026.
7. Database of failed startups, local export — /method/#dead (grade C). Local export. AI-written summaries, not independently verified. Source for the failed predecessors.

Contact: aiolum@livyden.com. Run Lark? Send corrections or a verified figure to aiolum@livyden.com (subject: Correction: Lark).