Skip to content

AI Data, Infrastructure and Agents

Build AI on Trusted Business Context, Not Raw Data

AI initiatives fail when business data is fragmented, inconsistent, and disconnected from how the company actually operates.

Discern provides the AI transformation infrastructure that turns CRM, billing, ERP, Product, and operational data into trusted business context, powering AI agents, automation, and decision-making at scale.

From semantic data layer and AI-ready metrics to agent development and data quality audit and governance. Discern helps B2B companies move from AI experimentation to production.

Discern AI - Production-Ready AI Agents for Revenue Operations

The Missing Layers Between Enterprise Data and AI

Most companies are investing heavily in AI

Yet the majority of AI projects struggle because:

  • Business data is not pre-calculated and is inconsistent within or across systems
  • Critical metrics are defined differently across teams
  • AI lacks business context
  • Data quality issues undermine trust
  • AI costs increase as context windows grow
  • Agents become difficult to maintain over time

AI models are improving rapidly

Business context remains the bottleneck:

  • AI Transformation Infrastructure — Discern solves this problem by creating the foundation layers required for enterprise AI adoption
  • Business Context Layer — Transform raw operational data into trusted business definitions, relationships, KPIs, and calculations
  • Semantic Data Layer — Thousands of pre-built or real-time business metrics across lead, pipeline, retention, and operations
  • AI Agent Infrastructure — Build, deploy, monitor, and maintain AI agents powered by trusted business context

100% Accurate Business Metrics

AI retrieves trust calculations rather than recreating business logic. Every team and every AI system operates from the same definitions.

Faster Time to Production

Move from AI pilot projects to production-ready deployments in weeks instead of months. Business context, metrics, and operational logic already exist.

Generate Recommendations

Lower AI Infrastructure Cost

Enables models to work with a smaller, more structured context, reducing token usage, model calls, and compute requirements.

Faster AI Responses

AI agents retrieve calculated, business-ready metrics directly rather than processing raw operational records at each query time.

Reduced Hallucinations

Business definitions, KPI logic, and relationships are already encoded within the semantic layer. AI works from trusted context instead of assumptions.

Governance & Auditability

Every output can be traced back to underlying business logic, calculations, and source systems. Build trust while maintaining control.

Four Core AI Transformation Services

Week 1 Define

AI-Ready Semantic Business Layer

Discern transforms operational data into a semantic business layer containing business definitions and thousands of calculated metrics. Examples include:

  • ARR/MRR/GRR/NRR
  • Churn Risk
  • Conversion Rates
  • Pipeline Coverage
  • Sales Cycle
  • ASP
  • Marketing ROI
Week 2 Build

AI Agent Development & Operations

Discern designs, deploys, and maintains AI agents that support real business workflows. Examples include:

  • Data Quality agents
  • Rep Coaching agents
  • Customer Retention agents
  • Cross-sell / Upsell agents
  • Deal Inspection agents
  • Pipeline movement agents
Week 3 Test

Data Quality & AI Governance

AI can only be as reliable as the underlying data. Discern continuously identifies and helps correct:

  • Missing fields
  • Duplicate records
  • Revenue attribution issues
  • Pipeline inconsistencies
  • Broken hierarchies
  • Process violations
Week 4 Launch

End-to-End AI Infrastructure

Discern helps companies build the complete foundation for enterprise AI, including:

  • Data pipelines
  • ELT architecture
  • Data warehouses
  • Semantic layers
  • Governance frameworks
  • Agent platforms

AI Agents, Powered by Discern Intelligence Modules

Every Discern AI agent is built on top of one of our proven intelligence modules. The agent inherits the module’s data transformations, business logic, and metric definitions — ensuring Investor-Grade Truth™ in every output.

Cross-Sell / Upsell Agent

Which customers are ready to grow — and what should we offer them?

  • Analyzes subscription mix, product usage, and account profile (segment, size, industry, stage).
  • Matches patterns against expansion playbooks to surface high-propensity targets.
  • Creates prioritized Salesforce opportunities for the account team, biweekly or monthly.

Output: Ranked expansion accounts, recommended products with rationale, auto-created CRM opportunities.

Data Quality Agent

Can we trust the data in our source systems?

  • Scans CRM, billing, and subscription records for hygiene issues — overlapping subs, gaps, and stale contacts.
  • Verifies company names, domains, and contact employment against external reality, and flags changes.
  • Routes exceptions through a human-in-the-loop queue, then writes approved fixes back to source.

Output: Exception queue, approved write-backs to CRM and billing, full audit trail of every change.

Pipeline Health Agent

Do we have enough pipeline to hit our targets?

  • Continuously evaluates pipeline coverage against bookings goals.
  • Analyzes coverage ratios by segment, region, and team.
  • Applies historical conversion rates and velocity trends.

Output: Clear “on track / at risk” signals, root cause breakdown, recommended actions.

Funnel Performance Agent

Where are deals breaking down in the funnel?

  • Analyzes conversion across every stage of your sales funnel.
  • Tracks stage-by-stage conversion rates and velocity.
  • Flags statistically significant deviations from historical norms.

Output: Real-time red flags, root cause analysis, targeted conversion recommendations.

Rep Productivity Agent

Which reps are on track — and who needs support?

  • Evaluates rep-level performance across pipeline activity, conversion, and outcomes.
  • Benchmarks against team averages.
  • Identifies reps at risk of missing targets early in the quarter.

Output: Rep scorecards, early intervention alerts, data-driven coaching recommendations.

Deal Inspection Agent

Which deals are real — and which are at risk?

  • Performs deep deal-level analysis to assess quality, risk, and likelihood of closing.
  • Evaluates progression, activity, and engagement signals.
  • Detects stalled or at-risk deals.

Output: Deal-level risk scoring, prioritized “deals to inspect” list, suggested actions.

From AI Experiments to AI Adoption

Most companies start with AI agents with MCP servers. Successful companies start with AI infrastructure. Discern provides the trusted business context, semantic data layer, governance framework, and operational expertise required to make AI work at scale.

Reliable, governed, and high-quality data provides the foundation for accurate analytics and AI-driven decisions. Use Discern to prepare business-ready data for AI. Access it through MCP or sync it back into your warehouse.

A semantic layer enriches data with business definitions, metrics, and relationships that make it meaningful and actionable.

Leverage business context to understand, reason, and respond using consistent business logic rather than raw data.

Context-aware AI delivers faster insights, better decisions, and measurable improvements in business performance.

Connect your CRM and get access to Discern’s out-of-box AI agents — free. See pipeline health signals, deal risk scores, and data quality alerts in minutes, not months.

Ready to Build AI That Actually Works?

AI agents that actually work — built on decision-ready data, not raw inputs. Pipeline health, deal inspection, data quality automation, and proactive insights.