AirBills: Scaling Payment Automation to $6M ARR.
AirBills needed a B2B utility management platform able to carry $1 million in daily transactions, and needed it inside 30 days. The constraint was not the architecture. It was that a small team had to stand up a product, an operations capability and a payment engine at the same time, on a deadline set by the market rather than by engineering.
3 CLIENTS ONBOARDED IN MONTH ONE · $70K PROCESSED
~USD 28,000 / MONTH OF MANUAL OPERATIONS REMOVED
BUILT FOR $1M IN DAILY TRANSACTIONS · 24/7 UPTIME
A 30-day deadline, and four bad ways to meet it
A working platform in 25 days
AI applied where the manual load actually was
From $0 ARR to EBITDA-positive
Have a deadline the
usual options cannot meet?
Questions about this engagement
Why not hire, or use an agency?
AirBills weighed both. Hiring one or two developers meant spending the deadline on alignment and team-building. An agency raised accountability questions the founders were not willing to carry on a payments product. The existing workforce had productivity and maintenance problems already, and freelancers introduced IP ownership and platform access risk. What was needed was a dedicated team that behaved like an in-house one and could be held to the outcome.
How was a working platform delivered in 25 days?
By treating the transaction ceiling as the design constraint from the first day rather than as a later scaling exercise, and by keeping frontend, backend engine and API integrations moving in parallel with one accountable team. The deadline was 30 days; the working version landed in 25. Feature development continued from there through several rounds of changing customer requirements.
Where did the AI actually get applied?
To the manual operations load, not to the product surface. Bill ingestion, matching and review scale linearly with properties and billers, and were consuming the operations team. Automating that work removed roughly USD 28,000 per month of manual effort and freed the team to onboard new product customers, which is what made the move to product-market fit possible.
What happened after the platform shipped?
The engagement continued through four phases: product build, then operations capability in early 2024, then product-market fit between March and July 2024 with Vacasa, AvantStay, PadSplit and Patriot Family Homes onboarded, and then optimisation and growth. AirBills reduced its burn rate through the partnership and tracked toward break-even by the end of 2024. iAastha still works with the founders.