Prepared for Boli AI
A read on where AI actually fits in Boli's stack, and where simpler layers would ship you faster.
You walked into eMerge this year the same way you did last year. EffectiveSoft left you a clean discovery package. The waitlist is still the product. The gap between those two facts is the interesting problem.
Our view
Most of what has to happen next for Boli is not AI. It is an orchestration problem.
EffectiveSoft scoped AWS serverless, DynamoDB, RDS, Kubernetes, Auth0, Interactive Brokers integration, five to ten algorithmic strategies, a 10-to-12 person implementation plan. The plan is good. Drawing the right lines before implementation restarts is the difference between shipping in six months and landing here again in 2027.
Traditional code and database plumbing
Account sync with Interactive Brokers, trade state, position management, audit log, user onboarding, investor reporting. Postgres and queue work, not model work.
Rule-based logic, legible by design
Your five to ten strategies are rule-sets dressed as algorithms. They should be legible as rules so LPs and compliance counsel can read them without an ML background.
The AI surface, wherever a learned model earns its seat
Signal generation, interface reasoning, or something adjacent. One layer, earned on merit, priced against the cost of running it. Not the whole brand, just the piece that pays for itself.
The engagement
A scoped sprint modeled on work we did for Feeld (CTO-led engagement).
You get a structure that tells you what to build in-house, what to route to a partner, and what to delete from the plan.
What ships in four weeks
- Two-day workshop on your stack and decision layers
- Four advisory calls across the engagement window
- A written Organizational Context Architecture tailored to Boli
- A Strategic Operations Framework you can hand to the next CTO you hire or the next contractor team you brief
Scoped sprint. Audit-first. Deliverable format is readable by a solo founder today and by a full engineering team when you hire one.
Methodology
Interpretable Context Methodology. Published, MIT-licensed, and readable as a spec.
Agent and system context organized as a layered filesystem. L0 identity down through L4 working artifacts. Measurable interpretability. Reproducible across teams. For Boli it reads as a spec: here is how a two-person technical org holds a live trading system in their heads without drifting.
Implementation partner
For the layer below orchestration, Eduba partners with NLP Logix.
Production data pipelines, trading infra hardening, broker-integration engineering. NLP Logix has been in machine learning since 2011 and runs over 150 data scientists. One introduction, no retainer drama, you meet them if and when the work calls for it.
Who you would be working with
Jake Van Clief, founder, on the sprint from day one as methodology author.
- 01Marine Corps veteran. Eight years, cryptographic systems, F-35 and F-18 avionics.
- 02MSc Future Governance, University of Edinburgh.
- 03Published in ACM TiiS (ICM) and arXiv.
- 041,500+ people trained across enterprise engagements since May 2025. Pacific Life, Colgate-Palmolive, KPMG UK (one of the Big Four).
- 056,000 to 9,000 hours saved per year on workforce enablement engagements. 95% 30-day adoption.
- 06Matt Creamer, CRO, runs the first conversation. Matt leads enterprise outreach for Eduba.
Next step
30 minutes with Matt Creamer. Bring the EffectiveSoft SRS.
We will map the 60/30/10 lines on your stack on the call, no prep needed. If the shape is wrong for where you are right now, the graceful move is a shorter paid working session or a warm handoff to NLP Logix. Either is fine.