TERSL/DB is the TERSL state storage and protocol system implemented at enterprise-class scale, reliability, and performance — and it's 100% compatible with local TERSL applications for agents. When AI state grows beyond single files and needs to be shared across multiple agents and AIs across the enterprise, TERSL/DB is the solution.
Tourbillon.ai builds and integrates AI-first semantic systems that are 100% compatible with all major agentic frameworks. Our services help take enterprises from AI ambition to running production systems.
An open hierarchical state language for humans and AI agents — readable like notes, queryable and patchable like data. Where JSON taxes every key and free prose resists safe mutation, TERSL sits between: the file is the state, and agents patch it by declaration instead of rewriting whole documents. The result: ~2.5× more token-efficient AI calls and responsibly less datacenter load per query.
{ "cases": [{ "id": 4412, "title": "outage", "priority": "high", "status": "open", "tags": ["billing", "auth"], "reporter": { "name": "Ada Reyes", "phone": "555-0100" }, "assignee": { "name": "Miguel Ortiz", "team": "platform" }, "summary": "Night shift lost auth to the billing API. Escalated to on-call at 02:31." }] }
# Cases ## 4412 outage(priority: high; open; billing; auth) reporter(name: "Ada Reyes"; phone: "555-0100") assignee(name: "Miguel Ortiz"; team: platform) """ Night shift lost auth to the billing API. Escalated to on-call at 02:31. """ // same state — now query & patch it by name: ? Cases.* [WHERE Its.priority == "high"] ## 4412 outage(+resolved; -open)
JSON taxes every key; free prose resists safe mutation. TERSL sits deliberately between — sparse enough to keep in context, structured enough to trust.
Readable like notes, queryable and patchable like data. No translation layer between what humans read and what agents act on.
Agents patch by declaration — what you don't restate, you don't change. Mutations are surgical, idempotent, and audit-friendly.
Start free and upgrade when it's running something real. Pay annually and save 20%.
// Speed covers request, write, and data-transfer limits — each plan absorbs short bursts above its everyday pace.
Applications we've built and released in the open — use them as they are, or as a starting point for your own.
A personal knowledge base an LLM incrementally builds and maintains — an AI that continually reads, organizes, and compounds your documents, acting as a self-updating librarian. It's the 1:1 port of Karpathy's llm-wiki pattern to TERSL: the same brain, with every bookkeeping structure typed, queryable, and linted for free.
tersl-brain on GitHub ↗
// benchmark — tersl-brain vs Karpathy llm-wiki, out of the box · same 15 docs, 72 questions, 3 reps · same model & independent judge
Durable agent memory as a TERSL store — no embeddings, no pipelines, no vendor black box. One file you can open, diff, and edit with the same CLI your agent uses; every MCP-speaking host reads and writes the same bytes. The product is a prompt; the store is the framework.
tersl-memory on GitHub ↗Orchestrates Claude Code headless from Cowork. Cowork acts as the supervisor with full UI access; Claude Code runs silently in the background and messages back when the work is done. Delegate the build, keep the oversight.
github.com/lrh-tourbillon/code-boss ↗From first roadmap to production systems — for small companies through large enterprises.
Assess where AI creates real leverage in your business — and sequence the work so value lands early.
Wire models into the systems you already run: ERPs, CRMs, data warehouses, internal tools.
Purpose-built agents, pipelines, and applications designed around your workflows, not ours.
Clean, structure, and govern the data your models depend on before it becomes the bottleneck.
Policy, audit trails, and controls so your AI footprint stands up to scrutiny — internal and regulatory.
Your team, fluent in the tools. We build capability, not dependency.
// Full service catalog in progress — contact us to scope an engagement.
The first wave of AI was about proving it could be done. The new wave is about doing it well: systems that are efficient by design, accountable by default, and measured in outcomes rather than demos. We build products that strip waste out of every model call, and we deliver the engineering that gets organizations — from small companies to large enterprises — from AI ambition to AI in production.
Less spectacle. More mechanism.
We built Tourbillon because we were inspired by its real-world counterpart: a watchmaking "complication" invented to cancel out the errors gravity introduces — a mechanism whose entire purpose is precision under real-world conditions. That's the standard we hold our work to.
// Founders
Whether it's a token bill that's grown teeth, an integration that's stalled, or an agent platform you need to trust — start the conversation.