The work is the deliverable.
No theory, no shelfware strategy. I build and ship the thing — then embed it into how the team actually works, day to day, until it sticks. An unused tool is a failed project, however elegant.
Most AI consultancies sell potential. This one is applied
Next Step Ventures is a boutique applied-AI practice for private markets and regulated firms. Not decks about what AI could do — working solutions built inside your real environment, within the tools, regulation and risk constraints you actually operate under.
In practice
01
About
NSV / LDN
Built by someone who has sat on your side of the table.
Next Step Ventures is led by James Bell, based in London. His background is inside private equity and private markets — living the deal workflows, the reporting cycles, the compliance realities — combined with deep, hands-on technical implementation.
That combination is the point. This isn't generic tech consulting bolted onto finance, and it isn't a finance CV reciting AI vocabulary. It's someone who understands both how the work actually gets done and how to build the thing — and who builds and shares that work in public.
The practice exists for one reason: the gap between what firms are told AI can do and what actually gets shipped inside their walls. Closing that gap is the job.
profile.json
Led byJames Bell
BasedLondon, United Kingdom
BackgroundPrivate equity & private markets
FocusHands-on implementation
Builds in publicLinkedIn ↗
02
Approach
Applied > theoretical
The difference between AI consulting that sells potential and applied work that ships.
Your stack, your permissions, your maturity.
Regulated firms rarely have access to the latest and greatest — some have Cowork, some only Copilot, most sit somewhere in between. Startups just want to move fast. Either way, my job is to find the best approach for your actual situation, not to demand you adopt something new.
Controls first-class, not an afterthought.
Adopting AI is as much about guardrails, policy and operating procedure as it is about tooling. I design the safe, defensible way to work — so what gets built survives contact with compliance, and with reality.
Real outcomes, honestly framed.
No inflated claims, no buzzword soup, no promises the technology can't keep. Where AI genuinely helps, we go deep. Where it doesn't, I'll say so — that's what makes the rest credible.
03
Services
5 lines of work
AI consulting services for private equity, private markets and regulated firms.
AI training for private equity firms and investment teams - practical sessions that teach AI through real workflows, real documents and the tools people already have access to. People leave able to do their own work better on Monday morning.
Hosted AI hackathons and structured working sessions that surface, prioritise and prototype the highest-value use cases with your team - so investment goes where the evidence points, not where the hype does.
Automated processes and agentic workflows, built and shipped. Local and self-hosted LLMs where data can't leave the building. Internal AI tools and apps, built quickly and plugged into the systems you already run.
The policies, controls and ways of working that let a firm adopt AI safely and defensibly — designed alongside the tooling, not retrofitted after something goes wrong.
Figuring out the right approach given your current stack, regulatory constraints and risk appetite — a clear-eyed view of what's worth doing now, what to watch, and what to ignore.
04
Ways to work together
Flexible by design
Engagements that flex to fit.
No big-bang transformation programme required. Start as small as a single afternoon, scale as far as an end-to-end build — and everything in between.
A session
A single hands-on AI training session or hosted AI hackathon with your team. One day, real workflows, working prototypes by the end of it. The lowest-commitment way to find out what applied looks like in your firm.
Best for — smaller houses, lean startups, and teams testing the water.
A build
End-to-end AI implementation of a prioritised use case: discovery, prototype, production, and the embedding work that makes it part of how the team operates - with the governance designed in from the start.
Best for — firms with a clear problem and the intent to ship a working solution.
A partnership
Ongoing AI advisory alongside your team: standing, practical counsel on stack decisions, new use cases, governance evolution and what's actually worth your attention as the landscape shifts.
Best for — firms treating AI as a durable capability, not a one-off project.
// The stack
Fluent across whatever you already run — Claude ChatGPT Gemini Copilot — and where data can't leave the building, locally-hosted and open models. Across all of it: automations, agentic processes, tooling implemented end-to-end, and the governance and process that make it stick.
05
Use cases
Illustrative, not exhaustive
Where applied AI earns its keep.
Every firm's highest-value use cases are its own. These are the themes where the work most often lands.
Communications
Taking the drafting burden out of high-volume, high-stakes correspondence.
e.g.Automated investor responses · LP query drafting · templated email workflows
Document review & interrogation
Reading at machine speed with an auditable trail behind every answer.
e.g.Data-room & CIM analysis · NDA and contract redlining · document comparison
Deal & pipeline workflows
Removing the manual drag from the processes deals actually run on.
e.g.Deal logging · pipeline tracking · briefing and memo drafting
Knowledge & research
Making what the firm already knows queryable — and what it doesn't, findable.
e.g.Queryable internal knowledge bases · thematic screening
Analysis & modelling
Getting structured data out of unstructured sources, and models that maintain themselves.
e.g.Data extraction & enrichment · spreadsheet and model automation
Internal tooling
Purpose-built software, at a fraction of the traditional cost and timeline.
e.g.Lightweight dashboards · agentic scripts built around existing systems
06
Blog
Field notes, sourced
Notes from the applied side.
Working notes from real AI consulting engagements - hackathons, private equity training, governance and adoption. No hype, sources at the bottom of every post. Start here:
30 Jun 2026
The gap between "AI can do this" and shipping it inside a regulated firm
Positioning
→
19 May 2026
How to run a use-case hackathon that actually ships something
Playbook
→
28 Apr 2026
What a three-hour AI crash course looks like
Training
→
09 Jun 2026
An unused tool is a failed project
Adoption
→
07 Apr 2026
Centralising knowledge: the one-stop shop your AI rollout is missing
Knowledge
→
View all posts →
> nsv --get-in-touch
Take the next step.
Whether you need AI consulting for a private equity firm, an AI hackathon host, a hands-on AI course for an investment team or a build inside a locked-down stack, the conversation starts the same way: what you're working with, what's getting in the way, and what applied would look like for you.