Our Services
15 years of data & BI expertise evolved into AI solutions that work - because we build on solid foundations
AI Strategy & Roadmap
Define your AI vision, assess organizational readiness, and create an actionable implementation roadmap that aligns AI capabilities with your business objectives.
Timeline: 4-8 weeks
Best for: Growth-stage companies and enterprises starting their AI journey or seeking to accelerate existing initiatives
What You Get?
AI & Data Readiness Assessment: Deep dive into data quality, governance, BI infrastructure, and organizational readiness - the foundations that determine AI success
Use Case Identification & Prioritization: Identify 20-30 potential AI applications, prioritize by ROI and feasibility
Technology Stack Recommendations: Right-sized platform architecture aligned with your needs and budget
ROI Modeling: Detailed business case with expected costs, benefits, and payback periods
Organizational Design: Team structure, skills requirements, and talent acquisition strategy
Change Management Plan: Stakeholder engagement, communication strategy, and adoption roadmap
3-Year Transformation Roadmap: Phased implementation plan with milestones, dependencies, and success metrics
Executive Presentation: Board-ready materials to secure buy-in and funding
AI Implementation & Deployment
Build and deploy production-grade AI solutions that deliver measurable business impact. We handle everything from data pipelines to model training to production deployment.
Timeline: 8-16 weeks
Best for: Companies ready to implement specific AI use cases with clear ROI
What You Get?
Custom ML Model Development: Train, test, and validate models on your data with 90%+ accuracy targets
Generative AI Integration: Implement LLMs (GPT, Claude, etc.) for content generation, analysis, or customer service
Data Pipeline & Governance: Build enterprise-grade ETL processes with data quality controls, governance frameworks, and BI integration - leveraging 15 years of experience
Feature Engineering: Extract and transform data into features that maximize model performance
Production Deployment: Deploy models to cloud infrastructure with monitoring, alerts, and failover
API Development: Create robust APIs for seamless integration with existing business systems
Model Monitoring & Maintenance: Set up tracking for model drift, performance degradation, and retraining triggers
Team Training: Hands-on training for your technical team to maintain and evolve the solution
Documentation: Complete technical documentation, runbooks, and knowledge transfer
AI Transformation Programs
Enterprise-wide AI adoption with multiple use cases, organizational change management, and the infrastructure to make AI a sustainable competitive advantage.
Timeline: 6-18 months, multi-phase engagement
Best for: Organizations committed to becoming AI-first with multiple use cases
What You Get?
Multi-Use Case Implementation: Deploy 5-15 AI solutions across departments and functions
AI Center of Excellence Setup: Establish internal team, processes, and governance to scale AI
Enterprise Data Platform: Build modern data infrastructure (data lake, warehouse, pipelines) to power AI at scale
ML Operations (MLOps): Implement automated model training, testing, deployment, and monitoring pipelines
Organization-Wide Training: Comprehensive programs from executive AI literacy to hands-on technical training
Governance & Ethics Frameworks: Establish policies for responsible AI use, bias detection, and regulatory compliance
Change Management: Full organizational change program including communication, training, and adoption tracking
Vendor Management: Evaluate, select, and integrate third-party AI platforms and tools
Continuous Optimization: Ongoing refinement, new use case development, and performance improvement
Executive Reporting: Quarterly business reviews with impact metrics and strategic recommendations
Featured: AI Revenue Intelligence
Our signature offering - a specialized AI implementation that transforms revenue operations for B2B companies. Powered by Inteliqx™ technology developed over 10 years of enterprise revenue analytics work.
Timeline: 8-12 weeks for initial analysis
Best for: B2B companies with $10M-$500M in revenue using Salesforce CRM
What Makes It Different?
After building revenue analytics systems for Dell EMC and RSA Security, we identified patterns that cost companies millions in hidden revenue leakage. We've productized these insights into an AI platform specifically trained on B2B revenue data.
Core Capabilities
Revenue Leakage Detection: Identify $500K-$3M in hidden revenue from pricing inconsistencies, duplicate accounts, and contract issues
Predictive Churn Analysis: Detect at-risk customers 60-90 days earlier with 85%+ accuracy using behavioral signals
Expansion Opportunity Identification: Surface $1M+ in cross-sell and upsell opportunities automatically
Customer Concentration Risk: Identify hidden relationships and concentration risks that impact valuation
Data Quality Monitoring: Continuous Salesforce data quality assessment and automated cleanup
Executive Dashboards: Real-time revenue intelligence with AI-generated insights and recommendations
Typical Results
20-30% reduction in revenue churn
15-25% increase in expansion revenue
$500K-$3M in identified revenue leakage
40-50% improvement in forecast accuracy
AI Practice Areas
💰 Revenue
Intelligence
AI-powered revenue analytics, churn prediction, pricing optimization, and expansion identification.
👥 Customer Experience AI
Intelligent chatbots, sentiment analysis, personalization engines, and predictive service optimization.
⚙️ Operations Optimization
Supply chain forecasting, demand planning, inventory optimization, and process automation.
📈 Marketing & Sales AI
Lead scoring, propensity modeling, content generation, campaign optimization, and forecasting.
🔍 Risk & Fraud Detection
Anomaly detection, fraud prevention, compliance monitoring, and predictive risk scoring.
📊 Business Intelligence
Automated insight generation, predictive analytics, NLP querying, and intelligent dashboards.
🤖 Generative AI
LLM implementation for content creation, code generation, document processing, and knowledge management.
💼 AI for Financial Services
Credit risk modeling, algorithmic trading, compliance automation, and customer segmentation.
🏥 AI for Healthcare
Diagnostic assistance, patient risk stratification, operational efficiency, and clinical decision support.