Sovereign models that beat the frontier at banking
Titan's family of Banking Models is trained specifically for the work of banking. Models are fully auditable and deployable inside your own perimeter.
One platform, three kinds of models
Titan's SLM
Titan's flagship banking small language model (SLM). Trained on regulatory guidance, supervisory examination material, and risk management. Built for accuracy on banking questions.
Titan utility models
Smaller, task-specific models that step in for narrow jobs like detecting personally identifiable information. Purpose-built for their one job, not for breadth or depth.
General-purpose LLMs
Secure access to a wide range of general-purpose models, including frontier models, for non-banking questions. Titan automatically routes to the right model for each task.
Intelligent model routing
Ask what the Reg E error resolution timeframe is, and your query is routed automatically to Titan’s flagship SLM. Ask what the current federal funds rate is, and you'll get real-time information from the right general-purpose model. Meanwhile, Titan’s context layer enriches every question with banking-specific context to deliver better results at a lower cost.
Purpose-built beats general-purpose
General-purpose models spread their training across thousands of domains. Titan’s flagship SLM trains on one: banking. When an answer comes down to the precise differences between Reg E and Reg Z, or the exact version of a regulation in effect on a given date, Titan is designed to get you the right answer.
Roughly 100x smaller than the frontier models it beats.
Average lead on the Banker Trust Index, vs. frontier models.
Average win rate in blind head-to-head evaluations against GPT, Claude, and Gemini, across 9,156 banking compliance questions.
Deployable in your own environment
Titan’s Banking Models come to your data, not the other way around. Choose a fully managed deployment or host models on your own infrastructure. Either way, your data never leaves your institution's perimeter, so data retention isn't a concern.
Model updates happen on your schedule, only after your own model risk management review.
Multi-tenant
Cloud-agnostic
Single-tenant
Dedicated private cloud
Self-hosted
Your own infrastructure
Titan’s Banking Models vs. general‑purpose LLMs
General-purpose LLM
