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The Digital Drill Ground for AI Risk Control - Unified Large Model Testing and Comparison Environment
Provides a unified large model testing and comparison environment for banks. In scenarios such as intelligent Q&A, customer consultation, loan approval, and marketing communication, through 'round-based' automated dialogue and task execution, uniformly evaluates key indicators such as task completion rate, hallucination rate, compliance rate, and response latency of different models and agents.
Build a 'headquarters-level AI benchmark evaluation platform' as a unified infrastructure for model selection and effectiveness acceptance. Without modifying the bank's core systems, through Mock technology, it builds a 1:1 simulated business environment, achieving 'test-driven adoption', helping the entire bank use large models more safely and cost-effectively.
Provides a universal 'round-based' testing framework that designs business processes as repeatable test scripts. The engine automatically drives scripts, conducts multi-round dialogues and task interactions with various models, recording each input/output, response time, and key decisions.
Basic Capability Evaluation: Tests general capabilities such as understanding, reasoning, calculation, and format compliance. Scenario-based Process Evaluation: Simulates real processes such as customer service, approval, and marketing through multi-role, multi-round dialogues. Prompt and Strategy AB Testing: Compares the effectiveness of different prompts and agent strategies under the same model.
Positive Sample Library: Precipitates high-quality answers, excellent wording, and compliance examples. Negative Sample Library: Collects problem cases such as hallucinations, serious errors, and non-compliant wording. Supports one-click addition of new online problems/good cases to the sample library for continuous upgrade.
Configurable indicator system covering accuracy, stability, efficiency, and compliance. Automatically generates project-level, model-level, and scenario-level reports for project approval, acceptance, and procurement materials.
Headquarters-level infrastructure + internal service mode, serving as a quantitative basis for model selection, project acceptance, procurement negotiations, and regulatory communication.
Business line project teams, technology departments, risk control and compliance departments. Supports both project evaluation services and self-service evaluation platforms.
Establishes standard test sets covering scenarios such as account opening, trading rules, product consultation, and investment advisory. Conducts multi-round dialogue evaluations of multiple models, focusing on accuracy rate, hallucination rate, compliance hit rate, response latency, and wording standardization.
Conducts intelligent customer service and credit approval robot evaluations for multi-vendor model and solution selection. Through large-scale boundary testing, ensures AI can maintain compliance boundaries and identify scenarios such as money laundering risks and politically sensitive persons.
Conducts sample co-construction and solution review around scenarios such as retail marketing wording and intelligent outbound calls. Optimizes prompts and agent strategies through AB testing to improve launch effectiveness and reduce rework.
Uses unified evaluation standards to support model procurement and external cooperation negotiations. Provides unified indicator systems, scoring rules, and report templates, with full traceability of the evaluation process.
Replaces single-project, one-time evaluations with a unified platform, precipitating exclusive sample libraries and indicator systems, improving the success rate and controllability of each AI project, and reducing business and compliance risks.
Shifts from 'testing model capabilities' to 'testing business usability', using indicators such as task completion rate, compliance rate, and hallucination rate to directly support project approval, selection, and acceptance.