Fintech Startup

A stealth fintech startup came to Aligned with real momentum: a working prototype, a repeat technical founder with a sharp thesis, and a co-founder with years of investment banking and corporate M&A experience already pressure-testing the idea across his network.

They did not need someone to tell them the problem was real. They knew it was. They needed three things before they could sell: a specific wedge to lead with, the right first customer, and what had to be true about the product to close them.

Across fifteen customer discovery interviews and six weeks of embedded product strategy, Aligned helped the team move from a broad and compelling opening position — AI for investment bankers — to a de-risked, sequenced path to first revenue: a validated wedge, a defined beachhead, and a shared understanding of what to build next and why.

The founding team built Excel export in from the start — that part was never in question. The harder question was whether users would stay inside their platform for the full workflow: raw data in, operating model out, scenario testing and valuation on top.

Fifteen interviews made the answer clear. Finance professionals do not use Excel as an output format — they use it as an environment. Iteration, assumption-checking, and scenario work all happen there. It is where deal teams have built years of muscle memory, and where the models they trust already live. Full UI adoption would have required behavior change and feature parity with a tool people have built careers inside. That adoption could come — but it would need to be earned through trust, not assumed from day one.

That reframed the product's job: not to replace the Excel workflow end-to-end, but to earn a place upstream of it. Get deal teams to a clean, trustworthy starting model as fast as possible — then hand off. Excel stays the system of record. The product owns the step before it.

A narrower claim. A far more executable one.

The founding team had warm relationships across investment banking, private equity, and corporate M&A. The question was not access — it was sequencing. Which segment could actually convert to a first paying customer, and how quickly?

The interview data across all three segments structured the comparison. Discovery mapped each against the dimensions that matter most at pre-revenue stage: procurement speed, deal frequency, buyer mentality, and how immediately the value proposition lands. Small-to-mid-market PE firms came out ahead on every axis — higher deal velocity, profit-center mentality, faster procurement cycles, and ongoing model maintenance needs that made the ROI tangible from day one. Large banks and corporate M&A teams showed genuine interest, but compliance-heavy procurement and infrequent deal flow meant conversion would be slow and hard to sequence.

Narrowing to small-to-mid-market PE was not a retreat from ambition. It was what the data pointed to — the fastest route to a first paying customer and a track record worth building on.

One of the most reliable traps in early product development is optimizing for the features that generate the most excitement in customer conversations, without asking who in the room is actually doing the work. Buyers and users often want different things. Building for the wrong one first is expensive to unwind.

Scenario testing generated genuine enthusiasm in discovery — consistently, across segments. But the enthusiasm came almost entirely from senior deal professionals: the people who evaluate opportunities, not the ones who build models. The analysts who would actually adopt the tool day-to-day had a more immediate pain — the time-intensive, repetitive work of setting up an initial operating model from scratch, often the better part of a day even with templates.

There was a second problem: scenario testing had a prerequisite. It either required ingesting existing Excel models cleanly, or native model quality that was not yet there. The sequence mattered.

Discovery reoriented the roadmap around the analyst's immediate pain: workflow acceleration at the pre-IOI screening stage. Faster initial models, fewer analyst hours burned evaluating opportunities that do not progress. That is a foundation scenario testing can eventually sit on — and a value proposition the actual user feels on day one.

Within a month, the team had enough conviction to align engineering around it. Not a pivot — a sharper point on a thesis that was already in motion.

The risk in any discovery engagement is that findings get documented, nodded at, and quietly set aside as the pace of building picks back up. The measure of whether discovery actually worked is not the quality of the readout — it is whether the team's day-to-day decisions look different afterward.

Aligned embedded structured ways of working designed to outlast the engagement: a beta readiness framework with defined gates from internal testing through warm lead pilots to general availability, shared criteria for what model quality had to look like before any external testing began, and persona-based test cases grounded in the interview data.

The signal that it held: that research later became the foundation for automated testing tooling the engineering team built internally. The discovery work was not filed away. It was absorbed into how the team operates.

The original hypothesis was coherent and technically ambitious: LLM-assisted finance work applied across the full deal workflow, modeled on what tools like Cursor had done for software engineering. Discovery did not challenge that — it stress-tested which part of the workflow was the clearest place to begin, and for whom.

The answer was pre-IOI screening: the moment when deal teams need a clean initial operating model fast to evaluate more opportunities without burning analyst hours. A specific, validated entry point. A buyer who can move quickly. A foundation the broader vision can build on as trust and track record accumulate.

That is the job of structured discovery at the pre-revenue stage: not to change what a team believes, but to give them the precision to act on it.