AI Lab

Working systems, safe boundaries.

Explore public demonstrations built to expose the reasoning, controls, and evidence behind a decision. Each experience states what is synthetic, deterministic, model-assisted, and human-controlled.
ATLAS-ENT-01Public demo · private production
Atlas Intelligence Enterprise synthetic Meridian workspace showing program signals, intelligence workflows, and the Atlas copilot

Agentic Systems

Atlas Intelligence Enterprise

An evidence-grounded program intelligence workspace that turns fragmented project artifacts into decision-ready intelligence through a coordinated network of specialist agents.

ModelInterprets evidence, compares artifacts, and drafts source-linked findings.

DeterministicSchemas, workflow state, access rules, evidence references, and audit history remain deterministic.

HumanLeaders review findings, resolve gaps, and retain authority over every consequential decision.

ATLAS-RISK-02Interactive demo · private local
ATLAS Risk Intelligence synthetic Northstar workspace showing enterprise risk, AI spend, optimization potential, model fit, and priority agents

Responsible AI

Risk Intelligence

An enterprise operating-intelligence workspace that connects AI-agent risk, economics, authority, and evidence so leaders can decide what to keep, optimize, restrict, or escalate.

ModelExplains patterns and helps users interrogate evidence behind an operating recommendation.

DeterministicRisk budgets, blast radius, residual risk, model fit, and change states are computed through explicit rules.

HumanNamed owners approve, reject, or modify every production change.

ATLAS-MTG-03Implemented MVP · synthetic data
Atlas Mortgage Intelligence synthetic dashboard ranking U.S. mortgage-market deterioration signals with scores, evidence, and component contributions

Product

Atlas Mortgage Intelligence

An evidence-backed mortgage-market intelligence workspace that ranks deterioration signals, explains their drivers, and preserves a verifiable record of how each conclusion was produced.

ModelRetrieves and explains evidence around deterministic market rankings.

DeterministicThe 0–100 deterioration score and component contributions are calculated without a model.

HumanAnalysts judge the relevance of signals; the system makes no borrower-level or lending decision.

EDGE-OPT-04Complete · private production
Options Edge public demo dashboard showing simulated market targets and ranked options candidates

Product

Options Edge

A completed, simulation-only command center that turns live market evidence into structured, explainable options decisions while keeping execution human-controlled.

ModelSupports contextual questions, research synthesis, and explanation of review states.

DeterministicMarket screening, policy gates, sizing constraints, and simulated accounting remain explicit and reproducible.

HumanThe user reviews the evidence and performs any trade manually outside the system.

EDGE-TRD-05Paper trading · safety-gated
EDGE Trading paper-trading interface showing account balance, trade tape, immutable ledger, reconciliation, and Ask Edge intelligence

Agentic Systems

EDGE Trading

A paper-trading control system that combines deterministic risk gates, immutable accounting, reconciliation, and permission-aware intelligence while keeping live-capital execution disabled.

ModelProvides read-only analysis and explains current paper-trading state.

DeterministicAccounting, reconciliation, risk limits, order-state rules, and authorization gates remain deterministic.

HumanLive execution remains disabled until explicit verification and authorization criteria are satisfied.

ATLAS-SPT-06Interactive demo
Atlas Sports Intelligence synthetic command center showing decision readiness, workspace health, and expert briefing

Product

Atlas Sports Intelligence

A multi-sport decision workspace that combines validated data, deterministic optimization, simulation, and explainable portfolio analysis.

ModelSupports explanation and interrogation of projections and scenarios where appropriate.

DeterministicOptimization constraints, portfolio exposure, and demonstration data are reproducible.

HumanUsers choose assumptions, constraints, and acceptable exposure; no outcome is guaranteed.