AI Agents
AI-Ready Data, Decision Intelligence, and Custom Agents for Revenue Teams
AI agents fail when the data beneath them is raw, fragmented, and poorly defined, as it often is in CRM, ERP, billing, and product systems.
Discern turns raw source data into AI-ready business data through labeling, definitions, transformations, and derived business metrics — delivered through our MCP server or written back to your warehouse.
On top of that foundation, Discern adds a decision layer for forecasting revenue across pipeline, funnel, and retention, and builds custom agents that analyze, forecast, recommend, and act using trusted business context.
What AI Agents Can Do
Every Discern agent is powered by two underlying systems:
- a data layer that creates labeled, defined, transformed, derivative business data
- a decision layer that models future outcomes and supports recommendations
Execute Multi-Step Analytical Workflows
Like a human analyst, AI agents gather data, apply business logic, run calculations, identify patterns, and synthesize conclusions — across multiple systems and time periods.
Monitor Performance Continuously
AI agents don’t wait for someone to run a report. They continuously analyze pipeline, revenue, and operational data — detecting anomalies and emerging risks as they develop.
Generate Structured Recommendations
Every agent output is structured and decision-ready: clear “on track / at risk” signals, root cause breakdowns, and specific recommended actions aligned to your KPIs.
Communicate Proactively
Insights are delivered where your team already works — Slack, Microsoft Teams, or email. No login required to stay informed.
Coordinate Across Systems
AI agents pull context from CRM, marketing, finance, billing, and product systems simultaneously. Actions and insights aren’t siloed — they reflect the full picture.
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 Idea to Production in Weeks
Week 1 — Define
Identify use cases. Align on KPIs and workflows. Specify agent behavior and output format.
Week 2 — Build
Integrate systems. Configure data pipelines. Develop agent logic and multi-step workflows.
Week 3 — Test
Validate outputs against historical data. Stress test workflows. Refine prompts and logic.
Week 4 — Launch
Deploy into production. Enable team workflows. Begin continuous improvement cycle.
How Customers Use Discern
Use Discern to prepare business-ready data for AI. Access it through MCP or sync it back into your warehouse for broader internal use.
Use Discern’s forecasting and modeling layer to understand where revenue is headed across pipeline, funnel, and retention.
Use Discern as the foundation for tailored agents that answer questions, monitor KPIs, surface risks, and support workflows.
Build Your First AI Agent
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 for AI That Actually Drives Decisions?
AI agents that actually work — built on decision-ready data, not raw inputs. Pipeline health, deal inspection, data quality automation, and proactive insights.