SAM Data Analysis & Scorecard Modeling Platform
Agents build the model.
People make the call.
SAM is our agentic, semi-automated data analysis and scorecard modeling platform for enterprises: a supervisor agent orchestrates seven specialist agents through a fourteen-step pipeline with fourteen named human gates — deployed on-premises and able to run on modest compute.
Try itTry SAM online: every feature, up to 10,000 samples
One supervisor, seven specialists, fourteen human gates
SAM breaks data analysis and scorecard modeling into fourteen auditable steps. The supervisor agent SAM-00 orchestrates project state, step dependencies, parameter budgets, re-runs and evidence; seven specialist agents work through the Step 0–13 pipeline, and three cross-step roles span the whole run — the Release Controller is the single gate to production.
- SAM-01Data contract
- SAM-02Variable analysis
- SAM-03Binning copilot
- SAM-04Model fitting
- SAM-05Independent validation
- SAM-06Scorecard packaging
- SAM-07Production monitoring
01Every number comes from deterministic code
WOE, IV, KS, VIF, PSI and every other statistic is computed by deterministic code inside a signed image. Any figure a model “works out in its head” is invalid evidence.
02A fourteen-step pipeline that invalidates itself
Steps 0–13 form a directed acyclic graph. Change any parameter, snapshot or binning and every downstream step — with its approvals — is voided. Only affected steps re-run; prior runs are kept intact.
03Fourteen named human gates
Every gate has a named signatory. Timeouts suspend the run; nothing passes by default. Cut-offs, limits and pricing are chosen by authorized people on signed documents — the agent offers options, people choose.
One team of modeling agents for every industry that decides with data
SAM’s method does not depend on the industry: if a business question can be framed as “predict an outcome from historical data”, the same fourteen-step pipeline takes it from analysis to modeling, validation and release.
Scorecards and strategies across the credit lifecycle
Application, behavior and collection scorecards, fraud-ring detection, limits and pricing, early warning.
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Measured decisions for members, marketing and channels
Member churn and campaign response models, distributor credit scorecards, diversion and rebate-claim anomalies.
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Auditable models for credit, compliance and safety
Customer credit scoring, promotional-spend compliance, pharmacovigilance signal detection and demand forecasting.
See the solutionEvery number can stand up to review
SAM rewrites the most error-prone, hardest-to-audit parts of modeling as deterministic engineering constraints.
Every statistic can be recomputed and traced
WOE, IV, KS, VIF, PSI and other statistics are computed by deterministic code in a signed image; figures “worked out” by a model are never accepted as evidence.
- Same data, same parameters — the same result every time
- Every number traces back to a code version and data snapshot
Change one thing, re-run only what it touches
Steps 0–13 form a directed acyclic graph: change any parameter, snapshot or binning and every downstream step — with the approvals it held — is invalidated. Only affected steps re-run; old runs are kept in full.
- Impact of every change is computed automatically
- Invalidated approvals must be signed again
Agents offer options. People choose.
SAM-05 validates in a separate workspace, with a separate sample and signing key. All fourteen gates have a named signatory, and the Release Controller is the only way any artifact reaches production.
- Developers cannot rewrite validation findings
- Cut-offs, limits and pricing are chosen by an accountable person in a named document
Four platforms, one line from data to decision
VDC answers where variables come from. SAM answers how models get built. DH S1 answers how models and LLMs run. The Enterprise Agent Platform answers how cognitive work moves to AI safely. All deploy on-premises, for every industry.
SAM Data Analysis & Scorecard Modeling
Agentic, semi-automated modeling with a fourteen-step pipeline and fourteen human gates — on-premises, on modest compute.
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Variable Derivation Platform
Time + product + status + value + statistic: turning detailed records into explainable features.
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Unified inference–training platform
Train while serving: statistical, machine-learning, deep-learning and large models deployed and trained together.
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Enterprise Agent Platform · Harness
Three layers and twelve components, fifteen Harness control modules and L0–L5 autonomy admission.
Learn moreEvery SAM feature, online, for up to 10,000 samples
Upload up to 10,000 records and run the whole fourteen-step pipeline — data contract to packaged scorecard, human gates included — to see for yourself whether SAM fits your business.
Algorithms and industry experience, side by side
More than ten world-class scientists and experts — leading researchers in machine learning and computer vision alongside senior risk leaders from JPMorgan, IBM, ING and other global institutions.
Dr. Qiang Wang
PhD in Robotics, Carnegie Mellon University; IEEE Fellow, researching large language models, machine learning and computer vision, anti-fraud and efficient model production. Formerly Principal Research Scientist at IBM Watson and chief systematic-trading expert at China Construction Bank; chief architect of our agent product family.
Start with one business question. Let SAM deliver a model you can sign off.
Whether you are in banking, FMCG and marketing, pharmaceuticals or another industry, try SAM online first — or talk to our modeling experts about your use case.