The challenge
Our client is an AI research product. It helps organisations gather and understand what their customers and audiences think, faster and more deeply than traditional surveys allow. Its founder built the first version and raised around $2 million from one of Australia's best-known venture capital firms.
That's a strong start, and it brings a familiar founder problem. A first version proves the idea. Turning it into a platform that customers rely on needs a full product and engineering team, and building one from scratch takes months of hiring, onboarding and management that a funded startup can't afford to lose. Shortly after launch, the startup needed that team in place.
The product challenges were demanding too. Research tools live or die on two things: how easily people can respond, and how much insight the business gets out of those responses. The startup wanted voice and text to work interchangeably, so respondents could answer in whichever way suited them. It wanted AI to turn piles of responses into clear insights. And it wanted to remove the slowest part of research altogether: designing the survey.
All of this had to come together in a product that felt simple to use, because the UX of the first version had grown as quickly as the product itself.
Our approach
Become the team
We took over as the startup's product and engineering team, with our team as CTO advisor. That gave the founder a complete, experienced team from day one, without the delay of hiring one.
Ship the features that turn a tool into a platform
We built two-way voice and text transcription, an insights engine that analyses aggregated responses, and an AI agent that creates a complete survey end to end with no user input.
Rebuild the experience
We streamlined the UX across the whole product so every new capability felt like part of one coherent tool. The stack combines Bubble, ElevenLabs, Anthropic models and a Pinecone vector database.
The results
The startup's survey acquisition now runs 6% above the industry standard. In research, small percentage gains in how many people take part compound quickly, because every additional response improves the quality of the insight a customer gets back.
The new features changed what the product can do. Respondents can answer by voice or text, which lowers the effort of taking part. Businesses get insights generated across all their responses instead of reading them one by one. And the survey agent turns what used to be hours of design work into a request, so customers can start research the moment they have a question.
For the founder, the biggest result was speed. Instead of spending months building a team, the startup had experienced product, design and engineering capacity from the start, plus CTO-level advice on architecture and AI choices. That let the company keep its momentum after the raise and focus its own energy on customers and growth.
For Lightning Ventures, the startup shows how we work with funded startups: we slot in as the team, combine the latest models with a fast build stack, and ship what the business needs next.
“It's all looking good. It really simplifies the overall flow for sure.”
What this means for your business
If you've raised money and outgrown a first version, the next step usually depends on having a strong team immediately. Hiring one takes months you may not have.
We step in as your product and engineering team, with CTO-level guidance, and start shipping straight away. We're deeply experienced with voice, retrieval and agent-based features, and we know which models fit which job. When you're ready to bring the team in-house, we hand over cleanly. If your roadmap is ahead of your team, let's talk.
