Platform Showcases

Concept Platforms

Demonstrating what's possible when architecture meets intelligence. Prototype systems showcasing our approach to building production-ready AI.

Financial Intelligence

Quantum Banking Neural Engine

Challenge

Regional banks need real-time regulatory insights to compete with larger institutions but lack the infrastructure and expertise to process complex SEC filings and FDIC data at scale.

Approach

Prototype platform integrating SEC EDGAR and FDIC data streams with LLM-powered analysis agents. Features custom board-pack generation with citation compliance and explainable reasoning paths.

Key Capabilities

Filing-to-insight pipeline: <15 minutes from publication
Multi-source data fusion: SEC, FDIC, call reports
Compliance-aware outputs with source citations
Executive dashboards with drill-down analytics

Key Insight

Speed and explainability are not mutually exclusive. When AI architecture prioritizes both, executive adoption follows naturally.

Industrial Intelligence

AI Intelligence Platform

Challenge

Manufacturing facilities face mounting downtime costs from unpredictable equipment failures. Traditional maintenance systems are reactive, not predictive.

Approach

Conceptual platform demonstrating real-time MQTT sensor ingestion, event-sourced CQRS architecture, and ML-powered anomaly detection. Automated work order generation based on predictive signals.

Key Capabilities

Predictive maintenance: Failure detection before occurrence
Real-time IoT integration: MQTT, Modbus, OPC-UA
Event-sourced architecture: Full audit trail
Cost optimization: Resource allocation modeling

Key Insight

The most powerful AI is invisible. When systems prevent problems before they occur, the technology fades into the background — exactly where it should be.

Agentic AI

FinRisk

Challenge

Enterprise regulatory workflows require complex orchestration across multiple systems, compliance checks, and human approvals. Manual coordination introduces delays and compliance risk.

Approach

Prototype regulatory workflow orchestration system with multi-agent coordination, automated compliance verification, and human-in-the-loop approval gates. Event-sourced architecture ensures full audit trails.

Key Capabilities

Workflow automation: Multi-step regulatory processes
Compliance verification: Automated rule checking
Audit trail: Complete event sourcing and versioning
Human oversight: Configurable approval gates

Key Insight

Intelligent automation amplifies human judgment rather than replacing it. The best systems know when to ask for help.

Agentic AI

Credentialed

Challenge

Modern hiring is broken. AI-generated resumes flood talent pipelines, work eligibility verification is fragmented, and employers can't distinguish authentic skills from fabricated credentials.

Approach

Dual-sided hiring platform connecting candidates and employers through verified skills. AI-graded assessments for documents, code, and media—paired with an Integrity Shield that detects AI-generated content and deepfakes. Privacy-preserving work eligibility verification stores results only, never raw PII.

Key Capabilities

Integrity Shield: AI-generated content and deepfake detection
Multi-modal assessment: Documents, code execution, video interviews
Privacy-first eligibility: Right-to-work verification without PII storage
Semantic talent search: Skills, scores, location, and eligibility filtering

Key Insight

In an era of AI-generated everything, authenticity becomes the ultimate credential. The platform that can prove what's real wins.

Logistics Intelligence

PricingBrain.ai

Challenge

Logistics pricing is reactive and margin-erosive. Rate quotes are disconnected from market reality, contract negotiations are manual and slow, and revenue leakage happens invisibly across thousands of shipments.

Approach

AI-first logistics pricing and revenue management platform. Dynamic rate engines analyze market signals, capacity data, and historical patterns to optimize pricing in real-time. Automated contract generation with intelligent clause negotiation accelerates deal cycles. Revenue management algorithms maximize yield across lanes, seasons, and customer segments.

Key Capabilities

Dynamic Pricing: AI rate engines responding to market signals in real-time
Contract Intelligence: Automated generation with smart clause negotiation
Revenue Optimization: Yield management across lanes, seasons, and segments
Margin Analytics: Visibility into pricing performance and leakage prevention

Key Insight

In logistics, the margin is made at the quote. AI that prices smarter—not just faster—is the difference between surviving and thriving.

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