"DYNAMIC DECISIONS NEED DYNAMIC DATA"
Create a direct contract path from:
[Discussion - Development - Deployment - Training - Operations]
- Proprietary AI Deployment
- Compliance Schedule
- Security Auditing Compliance
Equitus.us specializes in KoGen, knowledge generation with its - Knowledge Graph Neural Network (KGNN) which connects AI-ready data solutions, typically for enterprise, defense, and intelligence clients seeking to unify complex, disparate data sources generating a Knowledge Graph Ecosystem (KGE) which is the combination of all interconnected data.
A Proof of Concept (PoC) ladder is an excellent strategy to connect an enterprise with Equitus.us's advanced services by demonstrating concrete value at escalating commitment and cost levels.
PoC ladder, covering Pricing, Software, Development, and Deployment Support.
Enterprises can move from a low-risk, focused technical check to a high-value, full production deployment with clear decision points at each stage with KoGen.
1. PoC Ladder Structure & 3 Layer Pricing Model -
Starting for free (Registration) - Company Name - Name: Industry: Title: #of Employees: Country: System: Point of Contact: this process feeds into the "IST" Information Sizing Tool.
Generating a [Client] Pilot: NORMALIZATION, VISUALIZATION, ITERATION
PoC ladder is structured into three ascending stages, each increasing in scope, commitment, and cost. Hybrid Pricing approach, combining a Fixed Price for the clearly defined initial PoC phases and a Time & Materials (T&M) or Subscription/Value-Based model for the larger, more customized deployment stages.
| Stage | Focus/Goal | Pricing Model | Estimated Cost Range | Deliverable/Success Metric |
| Stage 1: Foundational Feasibility PoC | Prove the core technical capability of KGNN to ingest and unify a small, specific set of the enterprise's data. Goal: Technical Validation. | Fixed Price (SOW-based) | $25,000 – $75,000 | Automated creation of a functional, basic Knowledge Graph from 1−2 defined data sources; clear report on data unification success rate. |
| Stage 2: Targeted Value PoC | Prove business value by applying KGNN to a key, high-impact business use case using a larger, representative data sample. Goal: Value Demonstration. | Fixed Price + Optional T&M for custom integration | $100,000 – $250,000 | A working prototype integrated with 1 enterprise application (e.g., RAG-enabled LLM or analytics dashboard) that solves the defined use case; Quantifiable business metric improvement (e.g., reduced time-to-insight). |
| Stage 3: Pilot Deployment & Scale | Fully deploy the solution for a limited user group/department, with a robust architecture for scaling across the enterprise. Goal: Production Readiness. | Subscription/Value-Based (for KGNN software) + Dedicated Team T&M (for development/support) | $135,000 (for preconfigured KGNN appliance) + Ongoing T&M/Subscription | Fully integrated, optimized KGNN platform on-prem or in-cloud; a defined Production Support & Training plan; clear ROI projection for enterprise-wide scale. |
2. Software & Core Service Integration
KoGen is generated by creating a Normalization layer using Equitus.us's Knowledge Graph Neural Network (KGNN) platform, which is positioned as a rapid-installation solution for automated data structuring and AI-ready data.
| PoC Stage | Software & Services Utilized | Key Software Feature |
| Stage 1 | KGNN Platform (Trial Access/Basic Instance), Expert Rapid Resolution Consulting | Automated Data Unification: Demonstrates the ability to ingest and structure data from one or two disparate sources without complex, manual ETL. |
| Stage 2 | KGNN Platform (Prototype License), RAG for AI Consulting, Deep Data Mining (if relevant) | Semantic Contextualization: Demonstrates how the knowledge graph enriches data, enabling complex queries, relationship discovery, and enhanced RAG (Retrieval−Augmented Generation) for AI. |
| Stage 3 | Full KGNN Appliance/Platform License, Equitus Fusion, Video Sentinel (EVS) (if applicable) | AI-Ready DataQuery & Optimization: Full-scale platform features, ensuring stability, throughput, security (on-premise focus), and integration with existing enterprise security (Active Directory) and applications. |
3. Development and Deployment Support
The support offered must evolve from initial expert guidance to a full, dedicated deployment partnership. core software is
| PoC Stage | Development and Deployment Support | Key Activities & Milestones |
| Stage 1 | Initial Scoping & Setup | Activity: Data Source Identification and Access setup (e.g., connecting to a single S3 bucket or database). Environment setup (usually a small sandbox instance). Milestone: Successful ingestion and visualization of the small, unified data set in a basic graph viewer. |
| Stage 2 | Prototype Development & Integration | Activity: Development of custom semantic models for the use case. Building the integration layer (bidirectional with 1 app/LLM). Performance testing on the use case data set. Milestone: Successful execution of a 5 to 10 critical use−case queries in real-time with demonstrable accuracy/insight improvements. |
| Stage 3 | Production Implementation & Knowledge Transfer | Activity: On-Premise Installation by Equitus Expert Labs (or secure cloud deployment). Authentication/Integration with Active Directory. Training for the enterprise's technical staff and data engineers. Performance optimization for enterprise load. Milestone: Go-Live with the pilot user group. Formal handover documentation and 24/7 support contract initiation. |
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