AI engineering, end to end.
Rivoli AI is a small technology company focused on AI engineering. We build our own platform and tooling, with expertise across the full AI value chain. Our current focus is agentic platforms for software developers.
01
AI Engineering
We work across the full AI value chain — not only at the model layer, but in everything required to make AI systems reliable in practice.
02
Platform & tooling
We invest in our own platform and tooling rather than assembling someone else's. Owning the stack is what lets us iterate at the speed of our own decisions.
03
Agentic platforms
Today's focus is agentic platforms for software developers — work we use ourselves before anyone else sees it.
Mission
The practical frontier of AI is not raw model intelligence; it is disciplined agency — systems that stay inside the task until the work is done. Our mission is to build the platforms and tooling that make agentic systems reliable enough to depend on, starting with the place we live: the daily practice of building software.
We do this by working across the full value chain ourselves — owning the stack rather than assembling someone else's — then turning what we learn into products other engineers can pick up and use.
What we do
We design, build, and operate the platforms and tooling that agentic systems depend on. We think at the system level — not the model level — and we ship the integrations rather than the slideware.
Building reliable AI systems is not a model problem; it is a systems problem. Our experience spans the full value chain — from data and evaluation through deployment and operations — and that breadth is what lets us ship integrated products rather than glued-together fragments.
We build and operate our own platform and tooling. Owning the stack lets us change any layer without depending on someone else's roadmap, and gives us a substrate we can improve in days rather than quarters.
Decades of combined experience building software at scale — across financial services, consulting, and global delivery. We treat AI as a systems-engineering problem first, and every line of code is designed to be operated, not just demonstrated.
Small, senior team. Architecture decisions are written down and shipped, not archived. We dogfood our own platform on our own engineering work, and we measure in commits, not roadmaps.
Engineering principles
Four ideas that shape how we build.
01
Own the stack.
A glued-together pipeline of someone else's APIs is brittle. We build the routing, runtime, observability, and developer interfaces ourselves so we can change any layer without permission.
02
Disciplined agency.
Capability is the easy part now. The hard part is persistence — staying inside the task, recovering from dead ends, finishing what was started. Reliability is the product.
03
Engineering rigor.
AI is a systems-engineering problem, not a magic one. Architecture is written down, trade-offs are debated, and what we build is designed to be operated, not just demonstrated.
04
Build the thing.
We ship code, not decks. The site is static. The architecture is written down. The velocity is in the commit log. If a problem matters, the right answer is to build the smallest end-to-end version of the solution and run it.
About Us
A small team building the AI engineering platform we wanted but could not buy. We have done this kind of work — high-stakes systems, decisions under pressure, software at scale — in previous lives. Now we're building it for ourselves.
Ty Clinkscales
CEO & Co-Founder
Ty Clinkscales is the CEO and Co-Founder of Rivoli AI, where he leads strategy, execution, and client delivery. He brings a background in complex investigations, intelligence-driven operations, and tactical leadership, with extensive experience using advanced technologies to assess risk and uncover actionable insight.
Sami Ben Grine
CTO & Co-Founder
Sami Ben Grine is the CTO and Co-Founder of Rivoli AI, where he brings senior technical and architectural leadership experience across financial services and consulting firms, with deep expertise in quantitative equities management, AI engineering, and platform engineering. He has led technology strategy and delivery across global regions, including the Americas, Europe, and Asia, helping organizations build scalable, resilient, and data-driven platforms.
Contact
For inquiries, partnerships, or general questions, contact us directly. For long-form thinking from the team, the blog is the canonical channel.