Customer case study
Growing the platform, growing the impact: Lendahand's next step with AI
Lendahand's growth was limited by one thing: how fast a small, expensive investment team could research and write deal memos. With Aimable, that work now takes a fraction of the time, on their own templates, grounded in their own sources, and safe with confidential data.
The challenge
The growth paradox
Lendahand's problem was never demand. On its platform, thousands of retail investors lend to entrepreneurs and small businesses in emerging markets, through local microfinance banks. Good opportunities sell out fast. The constraint sits on the other side: bringing enough vetted deals in.
Every opportunity means an investment manager finding a bank, assessing it, gathering documents that are often messy, badly scanned, and written in French, Spanish or Cyrillic, running the numbers against Lendahand's own criteria, and writing it into a memo a committee can decide on.
The obvious way to grow is to hire. But managers are expensive and hard to find, take about six months to deliver a first opportunity, and even then move only three to four deals a year. The real time sink is not the judgement. It is the analysis and the writing. A screening memo took around four hours. A full investment memo took 40 to 60 hours of deep, uninterrupted work a normal week rarely allows.
“I want my investment managers to spend their time on building relationships and judgement, not writing a 20-page memorandum that an AI can do in 15 minutes.”
The solution
AI that fits your process, not the other way around
Old software forces you to reshape your team around the tool. Aimable works the other way. It spent the time understanding how Lendahand's investment process actually runs, then shaped the work to fit it, in weeks, not a six-month consultancy project.
The screening memo became a repeatable skill that produces Lendahand's memo in their own format, a Word document plus their own Excel model, with the calculations run in code so the maths is identical every time and each deal is checked against Lendahand's own investment policy.
Because every output is grounded, the team can validate it. The memo shows where each number came from and how it was calculated, so checking a figure is a quick look at the source. Sensitive data is protected before it reaches any AI model, so Lendahand no longer has to choose between speed and confidentiality.
On the very first run, the skill filled Lendahand's usual Excel templates and ran the quantitative eligibility test against their criteria in about ten minutes. Daniel expected that to be months away, if it was possible at all.
“It tells us where it gets the data from and how the calculation is done. It gives comfort and trust that what is produced is not a hallucination. It can easily be validated.”
The results
More memos get produced. Taking a first draft that is already 95 percent there to 100 is a far smaller hurdle than starting from scratch, so the number of memos the team presents has clearly gone up, and earlier hesitation is gone.
Not locked to one AI provider
Aimable works with any model, so a change at one provider does not put the work at risk. The same skills run on a different model without rebuilding.
Safe with sensitive data
Sensitive information is protected before it reaches any AI model, with a full logbook of what the AI did on every memo.
One safe place for the whole team
Lendahand now has one safe AI environment where teams work together on sensitive data, using their own sources and rules. They started with the investment team and keep building on that same foundation.
“Now there is no more hesitation. We found a safe way to do it, so we go full speed ahead and get the most out of AI for Lendahand.”
Curious what this looks like for your team?
Book a demo and talk to Pim Verschoor directly. Pick a time in his calendar and he'll show you live how work that takes days shrinks to hours, safely, even with sensitive data.