Draft and reason like the firm.
Distil a compact model on a firm's executed contracts, precedent and playbooks, so it drafts, redlines and advises in the firm's own style and risk posture, not generic boilerplate.
One private workspace with every model, every agent and your entire memory. A private model foundry that builds models from your enterprise data, then shares them with every worker. Point it at your hardest problems and turn AI into outcomes, inside your own boundary.
Launch WorkspaceAsk in chat, speak to it, or call the API. However your teams work, Stelia Workspace meets them there.
Crucible is a private model training lab. It takes your proprietary data, and trains, fine-tunes and distils a model that knows what only you know, on Stelia compute, inside a confidential boundary so your data and your weights never leave your control. Base model, to fine-tune, to distilled small model: the full loop, run as many times as you need. The finished model is handed back as a secure API endpoint to call directly, or as a UI inside your Stelia Workspace.
One capability of Stelia's Constellation, and it knows no boundary or limit. Any domain, any dataset, any jurisdiction, at any scale.
Distil a compact model on a firm's executed contracts, precedent and playbooks, so it drafts, redlines and advises in the firm's own style and risk posture, not generic boilerplate.
Train on internal trading, risk and research data without it leaving your jurisdiction, and distil a fast, private model that speaks your house view and stays inside your control.
Train specialised models on genomic and multi-omic datasets far too large and sensitive to move, bringing the model to the data rather than the data to the model.
Fine-tune open models on your proprietary research corpora, compound libraries and assay data to propose candidates and predict binding, inside a confidential boundary so the science never leaves your walls.
Fine-tune on de-identified clinical notes, guidelines and protocols to triage, summarise and support decisions, kept within the institution's jurisdiction and governance.
Train models on classified data, air-gapped and under your command, so a nation builds frontier reasoning on its own soil without a single byte leaving the perimeter.
Fine-tune on grid telemetry, weather and asset histories to forecast demand, generation and failure across the network, on infrastructure you control.
Build models on citizen and administrative data that must remain in-country, fully auditable, to deliver public services in the languages and terms people actually use.
Distil compact models on equipment manuals, sensor logs and maintenance histories for on-prem, low-latency use where every millisecond counts.
Continuum is an organisation's shared AI context: one living memory of everything it knows and every skill it has built, drawn on and added to by every person, model and agent as they work. Thousands of users and models sharpen the same context at once. The organisation stays in sync, and what it knows compounds.
Across a satellite operator, every engineer, analyst, agent and model shares one live context: telemetry, imagery, orbital models and every mission decision, added the moment it happens. A lesson learned on one satellite is known across the whole fleet within seconds, out of the thousands of contributions a day flowing into the same memory.
A fusion programme runs on one shared context that thousands of experiments, and everyone running them, feed in real time. Every physicist, control system and model reasons from the same live memory of diagnostics, simulations and results, so nobody starts from scratch, and every shot sharpens the programme.
Every researcher, assay and result across a drug-discovery lab flows into one context its people and models all share. Knowledge that used to sit in silos becomes common memory, updated the instant it lands, that any scientist or model can draw on, so the whole lab reasons from everything it collectively knows.