Monitors every open opportunity in your Sales Cloud pipeline 24/7. Detects stall signals before deals slip, auto-drafts personalised follow-ups for reps to send, updates stages based on engagement evidence, and alerts on accounts at risk — so your pipeline forecast is always honest.
100%
pipeline visibility
every open opp
< 24hr
stall detection
vs end-of-week reviews
40%
forecast accuracy
improvement
2×
deal velocity
with alerts
Typical build: 3-week sprint · Fixed price · Production-grade
Coverage
100% pipeline
Detection
< 24 hrs
Alerts
Chatter + Slack
This is the actual Agentforce configuration Kovil AI builds and deploys — not a diagram. Here is what runs inside every node.
Agentforce topic fires on a scheduled basis (configurable: hourly, daily, or on deal stage change). Every open opportunity in the pipeline is fetched with full context: last activity date, stage, close date, engagement signals, contact history, and Einstein Opportunity Score. No opportunity is missed — the agent scans the entire pipeline, not just flagged deals. The baseline run typically processes hundreds of open opportunities in minutes.
Atlas Reasoning Engine evaluates each opportunity against stall criteria configured during implementation: days since last email, days since last meeting, days since last Chatter post from the prospect, close date vs current date drift, and stage age (how long the opp has been in the current stage vs your pipeline benchmark). An opportunity flagged as stalled is not simply 'no activity in 14 days' — the agent cross-checks engagement signals, including email opens and website visits from Data Cloud, to distinguish true stalls from quiet prospects who are still engaged.
For each stalled or at-risk opportunity, Einstein Opportunity Scoring runs a health score: probability of close, predicted close date, and risk tier (low/medium/high). The score incorporates: historical win/loss patterns for similar deals, rep engagement patterns, deal size vs average, contact engagement depth (number of contacts reached vs typical multi-thread requirement), and competitor mention signals from notes and emails. High-risk deals are escalated; medium-risk deals trigger rep alerts; low-risk stalls trigger automated nurture.
For every at-risk or stalled opportunity, Prompt Builder generates a suggested follow-up email for the assigned rep — grounded in the specific opportunity context: product discussed, last meeting outcome, any open questions from the last interaction, and the prospect's industry. The draft is not a template; it is generated fresh from live CRM data for each deal. The rep receives the draft in their Salesforce Tasks, reviews it with one click, and sends. This eliminates the 20-minute per-deal cognitive overhead of pipeline reviews.
High-risk opportunities trigger immediate alerts: a Chatter @mention on the Opportunity record for the assigned rep, a Slack DM to the rep with a summary of the stall reason and the suggested action, and a weekly at-risk digest to the sales manager with the full portfolio view. The Slack message includes: deal name, deal size, days stalled, Einstein risk score, last activity, and a one-click link to the opportunity in Salesforce. Managers see the same digest aggregated across their team's pipeline — without running a single manual report.
Where evidence supports a stage change — for example, a prospect who replied to outreach and confirmed a next meeting — the agent updates the Opportunity stage without rep intervention. All automated actions are logged as Activities on the Opportunity record with a clear 'Agentforce: automated' marker. This keeps the pipeline accurate without relying on reps to update stages manually. For deals that move backward (stall in a late stage), the agent flags for manager review before writing the stage change — preventing accidental pipeline compression.
Stall + risk reasoning
Evaluates each opportunity against configurable stall criteria and cross-checks engagement signals to distinguish true stalls from quiet but engaged prospects.
Deal health prediction
Scores deal health using historical win/loss patterns, engagement depth, and competitor signals — surfacing risk tier and predicted close date for every open opportunity.
Follow-up drafting
Generates a personalised follow-up email for each stalled deal — grounded in live opportunity context — ready for the rep to review and send with one click.
In-platform alerts
Delivers @mention alerts on the Opportunity record so reps get notified in-context, within Salesforce, without switching to a separate tool.
External rep alerts
Sends DMs and weekly digest messages to reps and managers — including deal name, size, days stalled, risk score, and direct links to Salesforce.
Engagement signal enrichment
Unifies external engagement signals (email opens, website visits) with CRM activity data so the agent can distinguish true stalls from low-touch active prospects.
Stage update automation
Executes the automated stage update logic with manager review gates — ensuring pipeline accuracy without relying on reps to manually update records.
Kovil AI scopes, builds, tests and deploys this Agentforce configuration end-to-end. You do not touch Agent Builder until it is live and monitoring your pipeline.
Stall criteria are configured per client during Week 1. Typical criteria: no email activity for X days (configurable per deal stage), no meeting logged in Y days, close date passed without update, stage age exceeding the pipeline benchmark for that stage, and contact engagement depth below multi-thread threshold. The agent cross-checks against Data Cloud signals — a prospect who is still opening emails is not treated the same as one who has gone dark. You control every threshold.
Yes — for forward movement (stage advancement where evidence exists). We configure the conditions carefully with you during implementation. Backward stage movement (where a deal stalls in a late stage) requires manager review before the change is written. All automated updates are tagged with an 'Agentforce: automated' marker on the Activity record, so reps and managers always know what the agent did vs what a human did.
We configure a Salesforce Flow that calls a Slack webhook when the agent flags a high-risk deal. The Slack message includes: deal name, size, rep name, days stalled, Einstein risk score, and a direct link to the Salesforce opportunity. We set up a dedicated #pipeline-alerts channel or use your existing sales Slack channels — your choice. Weekly digests are sent as a summary message on Monday morning.
It replaces the part of pipeline reviews where everyone is manually identifying what moved, what stalled, and what needs action. That work is done automatically before the meeting. Pipeline reviews become about strategy and deal coaching — not data archaeology. Most clients find their pipeline review time drops from 90 minutes to 30 minutes within the first month.
Book a 30-minute discovery call. We'll review your current pipeline review process, identify the stall signals costing you deals, and scope a 3-week fixed-price implementation.
3-week sprint · Fixed-price · Production-grade · Post-launch support included