Multi-Model Intelligence routes each task to the model that fits it, primary models for language, specialised models for query generation and classification, all deployable on-premise or hybrid, so Kollect*AI Agenta passes the architecture review.
Llama-based primary models handle language; specialised models handle query generation, classification, and summarisation; routing picks the right one by complexity, sensitivity, and latency.
CTOs, heads of data, and AI/ML leads at lenders and finance organisations who need flexibility on model choice, deployment topology, and data residency. For institutions where one-size-fits-all AI does not pass the architecture review.
Talk to UsModel choice, deployment topology, and data residency are configurable, so the platform bends to your architecture, not the reverse.
Each request is assessed for task complexity, sensitivity, and latency needs.
Model routing sends it to the primary or specialised model that fits.
Run on-premise or hybrid to meet data-residency requirements.
Models are evaluated continuously against operational outcomes, not just benchmarks.
Each capability works on its own and reinforces the others when combined. Continue through Kollect*AI Agenta.
