AutogenAI, a generative AI tool for writing bids and pitches, secures $22.3M

Business is regularly won and lost on the strength of a proposal. Now, a startup out of London called AutogenAI has built a tool based on generative AI that it claims can help businesses write stronger pitches to improve that strike rate, and it has won some money of its own: $22.3 million from Blossom Capital, which it is using to hire more talent, expand its platform and grow its customer base.

The investment values AutogenAI in the region of “hundreds of millions,” we understand from a source. It previously raised some $3.5 million.

As a measure of AutogenAI’s success, it’s managed to pick up 28 clients since it first opened for business less than a year ago.

And as a measure of just how guarded those customers are about the secret sauce they’re using to win their deals, and maybe the taboo that exists around using AI tools to replace or augment human work, AutogenAI is not disclosing a single actual customer name.

“There is still a feeling among customers that using AI would somehow detract from the quality of the work,” Sean Williams, the founder and CEO, said in an interview, explaining why no names are being disclosed.

(AutogenAI does note — in a press release that it proudly says was written by AutogenAI, it is a pitch after all — that the list includes “a global management consultancy, global BPO organisations, quoted and private construction companies and facilities management businesses, as well as charities and non-profits applying for grant funding.”)

Williams cut his teeth on years of working for some of the biggest private firms bidding to provide services to the U.K. government, an enormous business that collectively is worth nearly $500 billion annually.

Being successful in those tenders was a matter of experience, understanding what content to include and how to present it. But it was also a matter of budget: Those with the funds to invest in building strong bids regularly had a stronger chance of winning deals.

AutogenAI’s aim is to address both of these areas.

Williams said that the platform is built on an amalgamation of large language models — it uses LLMs from OpenAI and others, he said — combined with a client’s structured and unstructured proprietary data, and an interface developed by AutogenAI itself to help users query information and create pitches that in turn are based on a company’s most successful past work. These are then presented to the client’s team, which further tailors them — or potentially rejects them — before they are submitted to pitch for a contract.

In theory, one could ask ChatGPT to build a business pitch, but Williams response is that AutogenAI’s versions will be considerably more specific and thus ultimately more useful to its users.

“Companies like OpenAI are focused on AGI, super intelligence,” he said. “We’ve got a much smaller problem: We just want to help our customers win more work and work more effectively.” He estimated that AutogenAI’s software could speed up the process of writing a strong pitch “by 800%.”

That 800% speaks to the second area of winning bids, which is the required budget outlay. Williams estimates that some 10% of a total contract value can be eaten up by the cost of putting a bid together in the traditional way. His claim is that by using its tools it cuts down procurement costs by some 10%, improving the margins on those deals overall, with the time taken to write the first drafts of bids cut down by 70% and helping those working on bids to focus more on strategic additions.

Ophelia Brown, the founder of Blossom Capital, said that the firm was not yet using AutogenAI itself but that it planned to when it next raised funds. Its interest in the startup stemmed from the fact that while AI companies building LLMs are getting a lot of attention right now, those working on applications like AutogenAI are closer to where a wider range of businesses might make purchasing decisions.

“Where this gets¬†interesting is when you can see clear ROI on the spend for the product,” she said. “Companies are willing to pay for something that can help them save time and headcount.” That’s been proven out, she added, through its growth in its first nine months of business.