The AI teamyour fund doesn't have.
We build the systems that encode how your fund generates alpha. On your stack. Owned by you.
Across the full
investment lifecycle.
Every fund has its own way of generating alpha: the thesis, the network, the tooling, the playbook. We encode that into systems that run continuously, not just when your team has the bandwidth.
Investment teams spend much of their time on repetitive manual work: reading data rooms, building models in Excel, putting together IC decks, pulling comparables. AI is uniquely shaped for this work. Agents work in parallel, hold every prior deal in memory, stay consistent across the 100th document, and never tire. The judgement still has to be human; the preparation, synthesis, and surfacing don't.
The next generation of funds will treat AI like infrastructure, running continuously in the background. Most firms today are only AI-assisted: they bolt AI onto existing processes to do the same work faster. But faster work isn't sharper conviction. An AI-native firm is built differently: its systems change what the firm sees, how it reasons, and what it remembers, so knowledge compounds across deals and experience becomes a repeatable edge. That's where alpha is earned now.
Discover opportunities earlier, research them faster, and act with confidence.
Continuously scrape and monitor the online sources your strategy relies on (LinkedIn, Crunchbase, and more) to surface companies as they emerge. Filter down from 20,000 to the 200 that fit your thesis. From there, find the right contact, draft outreach in your voice, and run the sequence.
Compress the diligence timeline without losing the judgement that earns conviction.
Specialised agents read the data room in parallel, flagging inconsistencies and missing data, drafting first versions of IC memos and other documents, all informed by past deals. Your team reviews, adds judgement, and reaches a defensible position faster.
Stay close to every company without burning your team on data collection.
Financials and KPIs are pulled, normalised, and reconciled across every company, with anomalies surfaced automatically. Your team gets one view of the whole portfolio, so a lesson from one company informs the rest instead of each being managed in isolation.
LP communications and fundraising mechanics drafted from the same data that runs the portfolio.
Quarterly LP updates and decks are generated from live portfolio data, updates, and your track record. Answer each DDQ once and reuse it across every LP, so your team spends less time on fundraising admin and more on your next fund.
Every memo, deck, and note your fund has ever made, turned into lessons you can apply again.
Each decision is captured as it's made and linked to how it played out, so why you passed on a company resurfaces when it comes back around. Your firm's memory compounds, and it doesn't leave when people do.
Real-time pattern matching against everything your fund has ever seen.
When a new deal lands, the system surfaces the most relevant comparables and precedents from your own history, in real time, before anyone asks. Every decision draws on everything your fund has seen, not a public database or whoever happens to remember.
The shape of
every system we build.
Dependable AI is an architecture problem, not a prompting one. So we build from system-design fundamentals, not just a layer of AI agents on top of your tools. Agents read the source data and write structured outputs to a database your team can query, an interface inside the tools you already use is how your team interacts with the workflows, and a dashboard makes the system's health and usage visible. Documentation and secure hosting close the loop. Each part is replaceable; together they're real infrastructure, not a chatbot.
Underneath that surface, we organise the work into five layers: data, intelligence, workflows, interfaces, and enablement. Each engagement leans on a different mix, but the spine is consistent. We start at the foundation, so each engagement leaves groundwork the next one builds on. We finish at enablement: training your team and handing over ownership, so the system gets adopted and used long after we leave.
The foundation.
The most important layer, and the one everything else builds on. It re-architects your fund's data so it's legible to AI: deal data, portfolio metrics, and institutional knowledge, structured and connected. Nothing above can read, search, or reason without it, so every system starts here.
Custom systems you own,
not software you rent.
Every engagement is a fixed-scope project, defined by an outcome and built around how your fund actually works, because that's where your alpha lives, not in a tool every other fund can buy. No subscription, no multi-tenant platform, no off-the-shelf product behind it. Just one system, custom-built and fully owned by your fund.
The four attributes on the right are how we work in practice: custom, hands-on, project-based, and yours to own. Because it's built for you and owned by you, it compounds into an edge no subscription can give you.
Every system is shaped to your fund: your thesis, your criteria, your processes. Nothing is forced to fit a product's template, so it captures how you actually work, down to the details that give your fund its edge.
We work as an extension of your team, co-building the system with you rather than disappearing and returning with a finished product. Tight feedback loops and regular updates keep you close to what's being built, so you always understand it and can shape it as it comes together.
Every engagement is one shipped outcome on a fixed scope, timeline, and fee, not an open-ended retainer that drags on for months. It ships, the engagement ends cleanly with no lock-in, and you commission the next project only when it's worth doing.
The system runs entirely inside your own environment, on your infrastructure, servers, and data, with no Routine Labs server in the middle. You own all of it outright, the code included, so nothing has to move when the engagement ends.
Helping build the next generation
of AI-native funds.
Every investment team is already using AI. ChatGPT, Claude, or Gemini seats for the whole team, a platform pilot that quietly lapsed, a clever workflow someone built on a personal API key. It sits in pieces, and none of it compounds.
We think that's because the investment is going to the wrong layer. Picking a model isn't an edge anymore. Everyone has the same ones, and a subscription gives every fund the same generic product. What actually generates a fund's alpha is its thesis, patterns, processes, and judgement. That work lives in the heads of the people doing it, untouched by any model or subscription.
Routine Labs was founded to build that layer. We'd each seen the gap from a different side: one of us inside a fund, watching AI used as little more than a smarter search bar; the other building AI systems, seeing how far the capability had run ahead of how most companies were using it. The opportunity was huge, but the tooling, the systems, even the knowledge to capture it weren't there, and almost no one was building them. So we did.
We believe the funds that win the next decade will be the ones that treat AI as infrastructure, built into how they work, not just a set of bolt-on tools. We exist for the funds that want to get there first.
Josh O'Neill
Co-founderBackground in private equity. Brings the inside view of how a fund actually works and where it bottlenecks, so what we build stays anchored to a real problem.
Ron Schickendantz
Co-founderBackground in product and engineering. Brings the system-design and data foundations that every dependable build rests on.
Plugs into your stack.
Built on the best tool for each job.
We don't drag our own platform into the engagement. We pick the right component for the job, from the stack your fund already uses or wants to adopt, and wire it in.
Architecture is the
compliance story.
The strongest compliance posture is the one that has nothing to leak. We don't host your data, we don't aggregate across funds, and we don't train on what you share with us.
Code you own.
Every line we write lands in your fund's own environment. We don't run any infrastructure that holds your code.
Data stays at your fund.
No data flows to Routine Labs servers. Nothing trains on it; nothing aggregates across funds.
Residency where you need it.
We deploy to the regions your fund's compliance posture requires: EU, UK, US, on-prem. Wherever the data has to live, that's where the system lives.
Single-tenant by construction.
No shared database, no customer ID column. Isolation isn't a setting that can be misconfigured; it's how the system is built, so one fund's data can never reach another's.
Book a discovery call.
A 30-minute first call to talk through where your fund is with AI today, where you want to take it, and whether we're a good fit. If there's a project worth scoping, we'll find it together.
London-based · Project-by-project · You own everything