What data do you need to start?

Typically 12–24 months of platform history (opportunities, cases, invoices) plus the outcome you care about. No new data collection is required to get the first model live.

How do you keep recommendations trustworthy?

Every score ships with its drivers ('renewal risk: support volume up 3x, usage down 40%'), models are validated against held-out history before going live, and user feedback on each suggestion feeds the retraining loop.

Can AI handle confidential or regulated data?

Yes. We build models on encrypted data, train locally in your VPC when required, and never send sensitive information to third-party AI services unless you explicitly consent.

How often should you retrain models?

Quarterly is standard. As your business evolves, your customer profiles and win/loss patterns change. We monitor model accuracy, flag degradation, and retrain whenever signals drift from baseline.

What's the difference between predictive and prescriptive AI?

Predictive AI tells you what will happen (e.g., 'this deal will close this quarter'). Prescriptive AI tells you what to do about it (e.g., 'call the customer, surface their support ticket history, suggest a bundle'). We build both layers.

Enterprise Platforms

AI-Powered CRM & ERP Intelligence Layer that Predicts the Future

Supercharge your ERP and CRM systems with a cognitive intelligence layer that automates billing data entry, scores lead conversions, and forecasts revenue trends before they land.

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Beyond Basic Records

Storing transactions and logs is only a starting point; the true value lies in predicting operational outcomes. Manual cash-flow forecasting and reactive churn management lead to missed trends and lost customers. We overlay a predictive cognitive intelligence layer on your CRM and ERP platforms, scoring lead propensities and flagging billing anomalies. By surfacing next-best-actions inside standard records, we streamline the daily workflows your teams already run.

The Old Way

Passive Platforms

The Intelegencia Way

Intelligent Platforms

Reactive Decision Making

Predictive Sales Insights

Missed Sales Trends

Automated Fraud Detection

Manual Risk Analysis

Next-Best-Action AI

Static Forecasting

Dynamic Forecasting

Information Overload

Prioritized Workflows

Predictive Forecasting

Our machine learning models analyze historical sales cycles, pipeline velocities, and email engagement patterns inside your CRM. This predictive analysis outputs revenue forecasts that are significantly more accurate than traditional sales-manager assumptions. We help leadership identify deal slippage early, anticipate customer churn risks, and allocate resources based on statistical probabilities rather than gut feel.

Lead Propensity Scoring

Churn Risk Prediction

Automated Cash-Flow Forecast

Sentiment Analysis in CRM

Price Optimization Engine

Insights in the Flow of Work

A forecast that stays locked in an analyst's dashboard will not change sales behavior. We embed predictive opportunity scores and next-best-action alerts directly into the screens your reps use every day, from the opportunity page to the case queue. By displaying the specific factors driving each score, we help account managers prioritize high-propensity leads and address customer issues proactively.

In-Record Score Components

Explainable Recommendations

Action Buttons, Not Just Alerts

Feedback Capture per Suggestion

Role-Specific Insight Views

Automated Data Entry & Enrichment

Sales teams spend hours on manual record keeping that could be automated. We train AI models to extract information from email logs and calendar events, automatically creating contacts and populating opportunity amounts. When records arrive incomplete, our enrichment pipelines pull missing company details from public sources like LinkedIn and company registries, keeping your database accurate without manual toil.

Auto-Field Population from Email

Company Enrichment API Integration

Contact Deduplication Engine

Account Classification Automation

Data Quality Scoring

The Cognitive Stack

Intelligence Units

Four pillars that add intelligence: AI models that surface trends and insights from raw data, risk guards that flag fraud and anomalies before they cost you, action suggesters that guide reps on next best moves, and smart reports that auto-generate executive summaries.

Insight Bot

Surfacing trends from raw ERP data.

Risk Guard

Flagging suspicious financial transactions.

Action Suggester

Telling reps which deal to close next.

Smart Report

Auto-generating executive summaries of performance.

Anomaly Detection & Fraud Prevention

We build anomaly-detection systems that scan your transaction logs to flag irregularities before they affect your margin. Our models detect billing errors, duplicate vendor IDs, and suspicious payment adjustments inside NetSuite, along with sales anomalies like deals closing too fast. By setting up real-time alerting routes, each operational anomaly is instantly dispatched to the appropriate compliance officer for review.

Invoice Anomaly Detection

Deal Integrity Monitoring

Support Pattern Analysis

Cost Center Variance Alerts

Automated Remediation Workflows

The Upgrade

Our AI-Platform Roadmap

Five steps that move your platforms from reactive to predictive, covering data extraction, feature engineering, model training, UI-based insight injection, and continuous learning loops.

Data Mining

Extracting 12-24 months of platform history.

Feature Build

Identifying the variables that predict success.

Model Train

Training the AI on your specific business outcomes.

UI Injection

Placing AI insights directly into the CRM/ERP screen.

Continuous Learn

Updating models based on real-world wins/losses.

Measured Performance. Proven Growth.

Forecast Error

Lead Conversion

Churn Saves

Data Entry Time

Frequently Asked Questions
About AI-Powered CRM & ERP Intelligence Layer

Here you will find answers to questions we get asked the most about our offerings.

We augment those tools with custom models that look at external data (market trends, social) for deeper precision.