Ask anyone who has bid on a federal contract what keeps them up at night, and the answer usually is not the technical write-up or the compliance matrix. It is the price. Set it too high and a hungrier competitor takes the award. Set it too low and you win work that quietly loses money for years. The number sits at the center of every proposal, and for decades teams have arrived at it the same way: weeks of spreadsheets, a few phone calls, and a good deal of gut feel.
Revere, a startup in Y Combinator's Fall 2025 batch, wants to replace the gut feel with a model. The company builds AI agents that study a contract opportunity the way a rival bidder would - pulling labor rates, past awards, and hiring signals - and then estimates the odds of winning at each price you might submit. Internally the company runs under the name Tig Technologies Inc. To the market it goes by Revere, and its pitch fits on a bumper sticker: your unfair advantage.
The ProblemPricing in the Dark
Government contracting is an enormous market, and a strange one. Buyers are agencies, timelines run long, and the rules reward whoever can offer the most credible work at the lowest defensible cost. But the information a bidder needs to price well is scattered. Comparable awards live in one database. Labor rates live in job postings and public schedules. A competitor's likely cost structure has to be inferred from fragments. Assembling all of it into a coherent view of the field can take a proposal team weeks, and even then the final price often comes down to gut feel.
Increase pWin, protect margin, and give your team weeks back.- Revere, company site
That last line hints at the wedge. Revere is not trying to write the whole proposal. It is going after the single decision that most shapes the outcome and is hardest to get right: what to charge, and why.
The ProductFrom Fragments to a Probability
Revere's platform moves through three stages, each handled by agents rather than analysts. The output is not a report to read but a number to act on.
The Monte Carlo step is worth pausing on. It is a technique borrowed from physics and finance, where you run the same scenario thousands of times with slightly different assumptions to see the shape of the outcomes. Applied to a bid, it answers a question no spreadsheet cleanly can: given everything we can infer about who else is at the table, how often do we win if we price here?
Under the HoodReading a Rival's Rate Card
Much of the work is reverse-engineering cost. A competitor's price is built on labor categories - a program manager here, a systems engineer there - each with a rate, marked up by an overhead "wrap." Revere estimates those inputs from public signals. The sample rate ranges it publishes give a feel for the resolution it works at.
| Labor Category | Modeled Hourly Range |
|---|---|
| Program Manager | $72 - $96 |
| Senior Analyst | $48 - $66 |
| Systems Engineer III | $61 - $86 |
Stack those categories, apply an estimated wrap rate, and a competitor's opaque bid starts to resolve into a range. Do it across the likely field, feed it into the simulation, and the pricing decision stops being a leap of faith.
The DifferenceAn Agent, Not a Dashboard
Plenty of software promises government contractors better data. What separates Revere's approach is where the analysis happens. The old model hands you a dashboard and leaves the interpretation to you. Revere's bet is that the interpretation is the product.
The manual way
- Weeks assembling scattered intel
- Competitor pricing is a guess
- Final number set by gut feel
- Hard to defend in a pricing review
The Revere way
- Agents compile the field in hours
- Rivals' rates modeled from signals
- A pWin attached to each price
- A rationale you can point to
There is a quieter advantage too. Revere says each client pursuit feeds a proprietary competitive database that grows with use. The more bids the platform models, the sharper its picture of the field becomes - the kind of compounding edge that is hard for a newcomer to copy and hard for a customer to walk away from.
Your unfair advantage.- Revere
The MarketWhere Revere Fits
Revere lands in a young category of AI tools built specifically for federal contracting, alongside platforms such as GovDash that aim to modernize how contractors pursue and manage work. But Revere's real competition is the status quo: the spreadsheets, the manual research, and the instinct-based pricing that most teams still rely on. Its focus is narrower than a full proposal suite and, for that reason, sharper - it owns the pricing decision and tries to own it completely.
The founding team is small - Drew Taylor serves as co-founder and chief executive, working alongside co-founders Matthew Fan and Shreyas Chennamaraja out of San Francisco. That is a lean crew to take on one of the least transparent corners of the economy, which is roughly the point. The unglamorous verticals tend to have the least competition and customers who feel the pain most acutely.
Whether Revere becomes the pricing brain for government contracting or one option among several, its wager is clear enough: in a market where the winning move is a number, the company that models that number best has, well, an unfair advantage.