CRM automation that runs your pipeline while you sleep.

Every lead from every source — Meta ads, Google ads, your website form, WhatsApp conversations, email replies, referral programs, in-bound calls, marketplace listings — flows into your CRM automatically as a structured contact record. No spreadsheets, no copy-paste, no leads forgotten in an inbox.

Each lead arrives in the CRM with source attribution (which ad, which campaign, which keyword), enrichment data (company name, designation, website, location), an initial score, and a default owner assigned. Duplicates merge in real time. New conversations on existing leads append to the same record.

This is the foundation under every other CRM automation. Without clean, complete, attributable lead data, scoring and routing fail. With it, everything downstream works.

Every incoming lead gets scored on intent (how ready they are to buy), fit (how good a customer they'd be), urgency (how time-sensitive their need is), and budget (whether they can afford you) — then routed to the right rep automatically based on skill, territory, language, deal size, or whatever your routing rules require.

The scoring model is custom-built per business — for a real estate developer it weighs budget + location + timeline; for a SaaS it weighs company size + role + intent signals; for an education business it weighs course interest + start date + financial profile. We train the model on your historical conversion data so it actually predicts who'll close, not just who looks engaged.

Hot leads route in under 60 seconds to your most senior rep with full context attached. Warm leads route round-robin to the next available rep. Cold leads enter automated nurture and re-score weekly. The result: every rep is talking to the right leads, every day.

Deal stages should move automatically based on what happened, not based on whether a rep remembered to update the pipeline. This automation listens for real events — a contract signed in DocuSign, a payment received in Razorpay, a proposal opened in PandaDoc, a meeting marked complete in your calendar — and progresses the deal stage automatically.

When a stage hasn't moved in the expected timeframe ("Proposal sent" → no follow-up in 7 days), the system flags it for the rep with a contextual nudge. When a deal closes, it auto-creates the relevant downstream tasks (onboarding, invoice, kick-off call). When a deal goes silent, it triggers a re-engagement sequence.

The result: pipeline reports that reflect reality, forecasts that you can trust, and sales reps who never have to remember to "update the CRM" again — because the CRM updates itself.

Most leads die not because they weren't interested, but because nobody followed up on day 3. This automation creates the right follow-up task at the right time, on the right rep's task list, with the right context — automatically, based on the lead's stage, last interaction, and SLA.

A new hot lead → "Call within 1 hour" task. A proposal sent yesterday → "Follow up tomorrow if no reply" task. A meeting completed → "Send recap email today" + "Check in next Tuesday" tasks. A deal stalled at "Negotiation" for 5 days → "Reach out to break the silence" task. The rep opens their CRM each morning and sees exactly what to do.

For most sales teams, this single automation lifts follow-up consistency from ~40% (manual memory) to 95%+ (system-driven) — and lifts conversion rates roughly in proportion.

Every CRM accumulates duplicate contacts the moment leads come in across channels. The same person fills your web form, then replies to a Meta ad with a different email, then comes back through WhatsApp — and your CRM now has three "Suresh Kumar" records, each missing context from the others.

This automation detects duplicates in real time using fuzzy matching across name, phone, email, and signal patterns (same browser fingerprint, same WhatsApp number, same company domain). When it finds a match, it merges the records — combining conversation history, scoring, attribution, and ownership — without losing any data.

For high-volume CRMs (1,000+ new leads/month), this is the difference between a database you can trust and one you have to apologise for in every customer conversation ("sorry, I see you've spoken to someone before…").

Automated daily, weekly, and monthly pipeline reports that pull from your live CRM data, format for skim-reading, and explain what changed since the last report — delivered to your email and WhatsApp on a predictable schedule. No more Friday afternoons spent in Excel.

Daily reports cover yesterday's activity: leads added, calls made, deals advanced, closed-won, closed-lost, with rep-level breakdowns. Weekly reports add trend analysis, conversion-funnel views, forecast vs actual, and anomaly flags. Monthly reports go deeper with cohort analysis, lead-source ROI, and rep performance benchmarks.

For founders running 3–15 person sales teams, this is the difference between knowing exactly what your pipeline looks like every morning vs scheduling a 30-minute Monday meeting to find out. For boards and investors, it's a clean monthly export they can actually use.