Aurora

The problem

Product managers spend most of their week chasing context. The information they need to make good decisions is scattered across ticket trackers, design files, customer calls, analytics dashboards and long chat threads. By the time a spec is written, half of the evidence behind it has been forgotten or misremembered. Teams end up arguing about opinions instead of data, and the best customer insights rarely make it into the roadmap.

Why now

Product teams have adopted more tools in the past five years than in the previous fifteen, and each one holds a slice of the context a product manager needs. At the same time, retrieval and language models reached the point where software could reliably read across those tools and cite its sources. Companies were also under pressure to do more with smaller teams after years of rapid hiring. Aurora sat at the intersection of these trends: an overwhelming amount of scattered information, technology mature enough to organise it, and buyers motivated to make every product manager more effective.

The founders

Priya Raman led product at two developer-tools companies, where she watched talented teams lose days to status updates and spec archaeology. Felix Okafor built retrieval systems long before the term became fashionable, working on search infrastructure for a large enterprise software company. They started Aurora after Priya spent an entire weekend reconstructing why a feature had been prioritised, and realised the answer existed in a dozen tools but nowhere in one place.

Why we invested

Lina led the round because Aurora connected to the tools teams already used rather than asking them to adopt yet another workspace. The product read tickets, calls and metrics, then drafted specs with citations back to the original evidence, so every claim could be checked. In early pilots, product managers adopted it without any mandate from leadership, which is the strongest signal of real value in productivity software. Lina also saw that Felix’s retrieval architecture would get better as models improved, rather than being replaced by them.

How we helped

Lina joined Aurora’s board and spent the first year helping the founders decide what not to build. We introduced them to product leaders at twenty growth-stage companies, several of whom became design partners and later paying customers. Our platform team helped them run a structured security review early, which shortened enterprise sales cycles significantly. When they raised their next round, we supported the process with references and introductions to growth investors.

Where they are now

Aurora’s copilots now sit inside the planning rituals of hundreds of product and engineering teams. They draft specs, summarise customer feedback, surface the evidence behind roadmap decisions and keep stakeholders aligned without endless meetings. The company recently launched a feature that predicts which roadmap items are most likely to slip, based on patterns across past projects. Priya still writes her own specs by hand once a quarter, just to remember what the product is replacing.