The first wave of SaaS bundled every workflow into dashboards built for humans. Companies pay for 50 features, use 3, then hire consultants to connect the systems underneath.

That era is ending. Developers increasingly work alongside AI coding agents — tools like Cursor, Claude Code, and Copilot that read documentation, write integration code, and recommend APIs in real time. These agent-assisted developers don't need dashboards. They need functions. Clean, deterministic, well-documented functions they can call and trust.

Torium builds standalone APIs that do one thing with perfect accuracy.

Each primitive is extracted from a process that enterprises currently solve with months of consulting, manual spreadsheets, or overpriced software bundles. We find the deterministic core — the part that's pure data transformation, lookup, reconciliation, or validation — and ship it as an API with per-transaction pricing.

• Deterministic — Same input, same output, every time. No probabilistic guessing. These are functions where accuracy is non-negotiable.
• Extracted from a bundle — Currently trapped inside enterprise platforms that charge six figures for 50 features when you need one.
• Measurable ROI — The value of each API call is quantifiable. Days reduced, errors caught, dollars saved.
• Agent-friendly by design — Self-describing schemas, structured JSON, machine-interpretable errors. Built so an AI coding agent can read the docs, write the integration, and trust the output.

Per transaction. No seats, no tiers, no annual contracts. If an agent-assisted developer makes 10,000 calls a day, the pricing scales linearly. We don't penalize automation — we're built for it.

AI agents are changing how developers find and consume APIs. The cleanest, best-documented, most reliable function for a given problem becomes the default recommendation. We're building the APIs that agents suggest when developers ask "how do I solve this?"

The enterprises that rely on bundled software aren't going to unbundle themselves. The consultants who profit from integration complexity aren't going to automate themselves. We build the primitives that make both of those problems smaller — one function at a time.