We built this around the bid you don't write.

The number that started it

Teams that bid on everything that lands in the inbox win somewhere between 10 and 20% of the time. Teams that qualify hard — that walk away from most of what they see — win 40 to 60%.

That is the same firm, the same people, the same proposals. The only variable is what they agreed to write in the first place. Every hour saved drafting is real, but it is an hour spent on a bid that still has an 85% chance of going nowhere.

So the first thing Paavya does for a new customer is not write anything. It reads the RFP, scores it against what that company can actually prove, and shows the reasoning — including the reasons to walk away. Plenty of people find that a strange first impression from an AI writing tool. It is the entire point.

What we believe

• An AI that invents a fact is worse than one that writes nothing. Ask a general model for a certification date it does not have and it will produce one, confidently. On a security questionnaire that is not a typo, it is a disqualification. When a fact is not in your approved evidence, Paavya says so and asks. It does not fill the gap to look complete.
• A claim is only as good as its source. Every answer traces back to a document, with a date and the person who approved it. That is what makes automating a 400-question security review defensible rather than reckless — and it is what you show a procurement team that asks what tooling touched the responses.
• The tool should get cheaper to use, not more expensive. A chat session starts from zero every time. Your twentieth bid here should cost less than your first, because the library is denser and the answers already exist. Compounding is the difference between software and a subscription.
• Model quality is not a moat. Drafting quality improves every quarter no matter what we do. Anything we build that depends on models being bad is a business with a shelf life. Evidence, persistence and consistency get better as the models improve, not worse.
• Charge for outcomes, not headcount. Six to fifteen people touch a typical proposal. Charging per seat means a company pays more for involving its own experts, which is exactly backwards. Users are unlimited on every plan, including the $99 one.

Who we tell to go away

If you write fewer than five straightforward proposals a quarter, and you already know the answers by heart, use ChatGPT. A well-prompted general model will get you most of the way for about the price of lunch, and a platform is overhead you will resent by month three.

We would rather say that on a public page than take a quarter of your money and lose the referral. The customers this works for have enough volume that consistency stops being automatic — more than one person answering, security questionnaires running into the hundreds of questions, and claims that legal signed off on which nobody wants restated loosely.

Where we are honest about the limits

Paavya does not predict who will win a contract. It does not see private procurement information, and it does not have access to anything a buyer has not published. What it has is your evidence, the public record, and a scoring model whose reasoning you can read line by line and disagree with.

We will also tell you when we do not have the data. Claims about win rates on this site describe industry research into qualification discipline, not results measured inside Paavya. When we have enough customer outcomes to say something stronger, we will publish how we measured it.