Convey Raises $38 Million to Build AI Coworkers for Enterprise Office Tasks

Convey has raised $38 million in Series A funding to build AI coworkers for enterprise office tasks, as investors continue to back startups trying to move artificial intelligence beyond chatbots and into day-to-day business operations.

The funding round was led by Andreessen Horowitz, with participation from Khosla Ventures and Pear VC. Convey, founded in 2025, is building AI “teammates” designed to help companies automate repetitive office workflows such as invoice processing, financial reconciliation, campaign reporting, and ad-asset ingestion.

The company says its platform has already executed more than 1 million hours of background work. Its customer list includes companies such as NBCUniversal, Samsara, Unity, TelevisaUnivision, Faire, and ChargePoint.

The raise comes at a moment when businesses are under pressure to show real returns from AI investments. Many companies have already tested generative AI tools for writing and summarizing. Now the focus is shifting toward AI systems that can complete actual work inside enterprise operations.

Why Convey is getting attention

Convey is targeting one of the least glamorous problems in the modern office: repetitive operational work.

In many companies, employees spend hours moving information between systems, checking documents, preparing reports, cleaning data, and repeating steps that follow the same pattern every week. These tasks are necessary, but they often pull skilled workers away from higher-value work.

Convey’s pitch is that AI coworkers can take over more of these defined workflows. Instead of waiting for a user to ask a question, the system is meant to keep working in the background until a task is finished.

That is why the company uses the word “teammates” rather than only “agents.” The goal is not simply to automate one click or summarize one document. The goal is to give businesses AI workers that can own a repeatable process, follow rules, and deliver a completed outcome.

For example, a finance team could use an AI teammate to help process invoices or reconcile financial records. A marketing operations team could use one to prepare campaign reports or handle advertising assets. A large enterprise could use the system to reduce manual processing across departments where employees are stuck repeating the same steps.

Enterprise AI is moving from answers to action

The funding also reflects a broader shift in enterprise AI.

The first wave of generative AI was mostly about answers. Employees asked a chatbot to draft an email, summarize a document, explain a topic, or organize notes. That was useful, but it still left the human responsible for doing the actual work.

The next wave is focused on action. Companies want AI that can work inside business systems, use approved data, follow processes, and complete tasks without constant supervision.

That is a harder problem than generating text. Enterprise work is messy. Company data is often spread across different systems. Processes change. Approvals matter. Security rules cannot be ignored.

This is where startups like Convey are trying to create value. If AI can safely handle repetitive office work, the savings become easier to measure. Businesses can track hours saved, reports completed, error rates, or workflows processed.

That makes AI coworkers more attractive than generic AI assistants for many companies. The value is tied to completed work, not just a helpful response.

What businesses should watch

For businesses, the idea is appealing because many teams are being asked to do more without adding headcount. AI coworkers can help stretch existing teams by taking on routine work that is time-consuming but not deeply strategic.

But the promise depends heavily on execution.

An AI coworker is only useful if the workflow is clear, the data is reliable, and the system can be monitored. If a company has messy records, unclear approval rules or disconnected tools, automation can create new problems instead of solving old ones.

That is especially important for finance, compliance, customer data, and reporting. A wrong invoice or inaccurate campaign report can have consequences. Companies adopting AI coworkers will need guardrails, audit trails, and human review for sensitive work.

The best early use cases are likely to be narrow and measurable. A company should start with one repetitive process, define what success looks like, and test whether AI improves the outcome. Trying to automate too much too quickly could make the technology harder to trust.

Why the market is heating up

Convey’s funding shows how quickly the AI-agent market is expanding. Large software companies are building AI agents into their existing platforms, while startups are looking for specific office workflows where AI can prove its value faster.

Investors are paying attention because enterprise operations are full of repetitive work. Every large company has teams that spend time checking records, moving files, preparing updates, and managing routine requests. If AI systems can perform even a portion of that work reliably, the market could be large.

The challenge is that companies will not adopt these tools just because they sound futuristic. They will adopt them if they save time, reduce errors, cut manual work, or help employees focus on better work.

That is the real test for Convey.

A personal take

The most interesting part of Convey’s story is not that it wants to build futuristic AI coworkers. It is that the work it targets is ordinary. Invoices. Reports. Reconciliations. Asset workflows.

That is where enterprise AI may become useful first. Not by replacing the most creative people in the company, but by giving them more time to do the work they were actually hired for.