A to B

A to B with Cyrus from usehaven.com

The Hustle-First Accounting Platform at ~$10M ARR in 2 Years | Cyrus (useHaven.com) In this episode of A to B, I sit with Cyrus, founder and CEO of Haven. Haven is building a full stack accounting, tax, and finance platform with real-time support founders actually rely on. In roughly two years, Haven has grown to 600+ customers and is approaching ~$10M ARR, with product expansion underway across invoicing, banking, and AP automation. We go deep on: • How Haven took a “boring” category and made it feel modern, fast, and founder-first • Why GTM talent beats “industry incumbency” in accounting and finance • The community flywheel behind Startup Helpers and how trust compounds into distribution • Hiring philosophy: gut, pressure-testing, and matching pieces to the stage • Product focus: “clicks to value” and reducing friction to outcomes Metrics we unpack: • 600+ customers and approaching ~$10M ARR in ~2 years • ~700K net new ARR per month (across accounting, tax, tax credits, and upcoming products) • The roadmap: invoicing, business banking, and bill pay to automate the back office end-to-end The three A to B questions: • Hiring litmus test: gut + hunger + integrity, tuned by role • One growth lever: relentless GTM and obsessive customer outcomes • One product metric: clicks-to-value (how fast users get what they came for) If you’re building through noise, scaling with focus, or care about founder-grade execution, you’ll like this one. If you want to become more data driven, check us out at https://querio.ai [https://querio.ai]. Querio is the data platform the best teams use to win.

A to B with Patrick from Clarify.ai

The Autonomous CRM Racing to Series B With A Product Team of Engineers In Episode 2 of A to B, I sit with Patrick Thompson, cofounder and CEO of Clarify.ai [http://Clarify.ai]. Clarify is the autonomous CRM that actually does the work: it captures signals, creates next actions, migrates data, and keeps pipeline moving so reps can close instead of click. Clarify raised roughly $25M to date, grew to a 25 person team, ships daily, and is winning migrations from legacy CRMs. We go deep on: • Why Clarify launched early and chose a consumption model instead of per seat • How they win full CRM migrations from HubSpot and Salesforce • The culture choice to run without PMs early and make engineers own outcomes • Shipping speed as a growth lever and why their Series A was preempted • The intelligence layer that nudges follow ups and moves deals forward Metrics we unpack: • What progress in the system looks like: deals moving and fields updated • Adoption targets from thousands of weekly active users toward tens of thousands • Migration rate from incumbent CRMs and what it signals for Series B • How consumption pricing aligns revenue with real work done The three A to B questions: • Hiring litmus test: top 1 percent builders with ownership and product sense • One growth lever: speed to ship plus easy migrations that prove value fast • One product metric: autonomous actions that progress work and close deals If you care about AI native systems that collapse tools into outcomes, this one is for you. If you want to become more data driven, check us out at http://querio.ai [http://querio.ai]. Querio is the data platform the best teams use to win.

A to B with Will from Agree.com

The DocuSign Killer That Raised 10M In 13 Months With 7 People. In this first episode of A to B, I sit with Will Hubbard, founder of Agree dot com. Agree gives you unlimited free e signatures, then ties contracts directly into invoicing, payments and collections. No more sign in one tool and chase money in another. In about 13 months they: Raised 3M pre seed and 7M seed Grew to tens of thousands of users Ran it with a team of seven. We go deep on: Why signing and getting paid should never have been separate flows How they turned “free DocuSign” into a serious payments business The conference coffee cart stunt that helped kick off their first 10k users Why the product is naturally viral when one agreement has multiple signers How they handle support so everyone, including engineers, sees user pain instantly How they keep product quality high in a category with zero margin for error How they use AI coding tools without turning the codebase into chaos We also talk about the metric side: The main output metrics they care about now. Total contract value on Agree. Total payment volume flowing through Agree. Why the quality of customers matters more than the raw user count once the flywheel is spinning. If you care about fintech, SaaS or just building a tiny team that can punch way above its weight, this episode is worth your time. If you also want to be more data driven, check us out at querio.ai [http://querio.ai]. Querio is the data platform that the best teams on earth use to win.