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Multi-Model Intelligence · Kollect*AI Agenta

From One-Size-Fits-All AI to the Right Model per Task.

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.

Model Routing
On-Prem or Hybrid
Data Residency
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Multi-Model Intelligence
What Multi-Model Intelligence Does

One platform, many models, your topology.

Llama-based primary models handle language; specialised models handle query generation, classification, and summarisation; routing picks the right one by complexity, sensitivity, and latency.

04

Multi-Model Intelligence

Right model for the right task
  • Llama-based primary models for natural language understanding and generation
  • Specialised models for query generation, classification, and summarisation
  • Self-healing query layer when initial generation needs refinement
  • Model routing based on task complexity, sensitivity, and latency needs
  • On-premise or hybrid deployment options for data residency requirements
  • Continuous evaluation against operational outcomes, not just benchmarks
Who benefits

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.

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AI M1 M2 M3 M4
Multi-Model Intelligence includes
Llama-Based Models Specialised Models Model Routing Self-Healing Queries On-Premise Hybrid Deployment Data Residency Outcome Evaluation
How Multi-Model Intelligence Works

Four steps to fit-for-purpose intelligence.

Model choice, deployment topology, and data residency are configurable, so the platform bends to your architecture, not the reverse.

1

Classify

Each request is assessed for task complexity, sensitivity, and latency needs.

2

Route

Model routing sends it to the primary or specialised model that fits.

3

Deploy

Run on-premise or hybrid to meet data-residency requirements.

4

Evaluate

Models are evaluated continuously against operational outcomes, not just benchmarks.

Has one-size-fits-all AI failed your architecture review? We will walk through model choice and deployment options.
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The Rest of the Platform

Explore the rest of the platform.

Each capability works on its own and reinforces the others when combined. Continue through Kollect*AI Agenta.

01

Real-Time Insights

Live dashboards, automated reports, and proactive alerts on your operational data.

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02

AI-Powered Analytics

Prediction, risk scoring, and PTP forecasting that turn collections predictive.

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03

Natural Language Querying

Ask in plain English or Bahasa Malaysia; the agent writes the SQL and answers.

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05

Three Pillars of Trust

Accuracy, governance, and traceability, aligned with BNM and AICB principles.

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06

Use-Case Library

Six categories of ready-made prompts, from reporting to loss forecasting.

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Email:[email protected]
Phone:+603 8605 3378
Whatsapp:+6016-213 9873
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