system8.ai exists because the people who know how to do this are not the people writing the frameworks about it.
Steve Cannon spent 25 years inside the firms that figured out math-driven automation before anyone else did. Not advising them. Not consulting on their strategy. Building the infrastructure that made it work — the data engineering, the automation systems, the plumbing that AI sits on top of.
Interactive Brokers. Two Sigma. AQR. The Abu Dhabi Investment Authority. These aren't names on a client list. They're places he spent years doing the actual work.
In 2021 he took everything he'd learned inside those firms and applied it inside a real operating company — e-TeleQuote, a Medicare insurance broker with $79M in revenue and a $1–2M annual loss that no one could explain. His team built the model that found the answer. They identified exactly where the losses were coming from. The recommendation was precise and the data was clear.
The company didn't act on it. Leadership couldn't explain why the model was right, so they kept doing what they'd always done.
That experience — a working model, a failed project, the same outcome Steve had watched happen at companies that lacked the structure to act on what their data was telling them — is what system8.ai was built to solve.
Private equity has the structure. It has the controlling interest to push the recommendation through. The rigorous metrics to defend it. The patient capital to let it work. system8.ai helps fund managers use those tools — the ones they already have — to make AI actually work inside their portfolio companies.
From the firms that pioneered fully automated trading to the operators bringing AI into the rest of the economy.
Leading a team building a shared "AI base platform" and incubating Quant Portfolio Advisors (momentum-based investing strategies for private wealth) and AgoraBro (AI-driven admin and marketing for electricians, plumbers, and other trades).
Automated lead buying and lead routing using deep learning and linear optimization. Built and led a distributed data team across the US and Lahore. The hard-won lessons from this project inform much of the system8.ai playbook.
Launched the quant function at a major Middle-Eastern sovereign investor. Built the math-driven team for automated investing and modernized the underlying technology platform.
Hired and led a specialized "automation engineering" team. Refactored 400+ existing automated investing processes and built out the platform for AI, alt-data, and shorter-holding-time trading strategies.
Built the Big Data engineering team that enabled use of AI and deep learning across the firm. Co-winner of the Engineering Innovation award. Implemented Infrastructure as Code (IaC) — a foundation for the kind of flexible, AI-enabling engineering system8.ai now installs in PE portfolio companies.
One of the keys to fully automated trading is extremely high-quality data and data engineering. Built the complete framework for data ingestion and data quality automation that supported IB's industry-defining margin advantage — the same comparison cited on the Results page.
Built the back-end system for multimedia authoring and social sharing on one of the first platforms to bring user-generated multimedia to the web.
Built and guided the technology team — 85 engineers across 5 offices — delivering e-commerce back-ends with high-design front-ends for Tiffany & Co, the Museum of Modern Art, IBM, Sullivan & Cromwell, AT&T, and Microsoft's first e-commerce site.
The team that walks into your portfolio companies isn't assembled from a list. It's chosen for the work in front of it.
Every recommendation comes from someone who has actually shipped automation against real P&L — not someone who read about it. The work is real. The expectations are honest.
Every founding engagement is led personally. No handoffs. No project managers. No junior hours billed against the fund's investment. The expertise on the ground matches the work in front of it.
We understand organizational resistance — what it looks like, why it happens, and how to build the metrics that give leadership the authority to act anyway. That's the agency problem. Solving it is the job.
We build the deep supporting systems — data engineering, orchestration, lineage — that AI sits on top of. The glamorous work comes after the foundation is real.
Ready-fire-aim, not analysis-paralysis. We move on the obvious wins first while building toward the bigger ones. The fund doesn't get surprises buried in a status report.
system8.ai is in its early engagements. We're selective about which funds we work with and honest about what that means. If this is the right fit, the conversation will make that clear quickly.
There's no pitch deck. No proposal process. Just a direct conversation about what you're seeing in your portfolio and whether this is the right moment to act.