Daily delivery
8am
Before your morning stand-up, every weekday.
Use case · AI Automations·AI Automations
Numbers in execs' inboxes by 8am.
Pull metrics from every system, format a clean daily summary in Slack, email, or PDF, and deliver before stand-up. Every day.
- 8am
- Daily delivery
- 6+
- Sources merged
- 12hrs
- Saved / week
Setup in 1–2 weeks · Production-ready · Fully observable
weblink.builds · production
47 runs this week · all systems green
automation · daily-digest-v2
live · last run 6:30 AM today
Inputs · sources
HubSpot CRM847 leads
Linear issues42 open
GA4 + Plausible12 metrics
Stripe revenue₹4.2L MRR
running
Digest Engine
Claude + scheduling
Outputs · destinations
Email · founders6:28 AM
Slack #leadership6:30 AM
Notion · weekly6:32 AM
Client portals7:00 AM
recent activity · last 5 minutes
- 6:30 AM✓ Daily digest delivered · 8 stakeholders · 14 metrics summarized
- 6:28 AM✓ Anomaly flagged · MRR up 12% · narrative explanation included
- 6:25 AM⚠ HubSpot API timeout · retried 2x · used cached data from 5 AM
- 6:22 AM✓ Linear sync complete · 4 PRs merged overnight · summarized
- 6:18 AM✓ Weekly client report queued · Acme Corp · 9:00 AM delivery
showing latest 5 of 47 runs this week
The problem
Reporting is the meeting that shouldn't exist.
Every day, someone on your team copies numbers from 4 dashboards into a slide, pastes the slide into Slack, and answers questions about it for 20 minutes.
That's 5 hours a week per analyst, and the slide is stale by lunchtime. There's a better way.
What manual handling looks like
Form submission
Email to ops@
Spreadsheet check
Slack tag rep
~ 2–4 hours typical · sometimes days
The solution
Live data, daily summary, no analyst required.
We build a pipeline that pulls metrics from every system — analytics, billing, support, sales — runs your business logic on top, formats a daily summary with AI commentary, and delivers it to Slack, email, or as a PDF before your stand-up.
How it works
- 01
Collect
Pulls from analytics, CRM, billing, support, ops in parallel.
- 02
Compute
Applies your business definitions of "MRR", "churn", "qualified leads".
- 03
Narrate
AI drafts a 3-paragraph commentary highlighting moves and anomalies.
- 04
Deliver
Slack channel, exec emails, or PDF — pick your format.
The outcome
What this looks like in production.
Hours saved / week
12hrs
No more dashboard-copying.
Sources merged
6+
In a single human-readable summary.
Render time
<2s
From query to formatted Slack message.
What it costs
Transparent pricing. Outcome-tied.
Tier
Daily Reporting Pipeline
Engagement
From ₹1L
2–3 weeks setup
Optional retainer
₹40k/mo
monitoring & adjustments
Included
- Connection to up to 6 data sources
- Custom KPI definitions and rollups
- AI-generated daily commentary tuned to your tone
- Slack, email, and PDF outputs
- Anomaly detection with alert routing
- Self-serve drill-down dashboard
- 30 days of post-launch monitoring
Tech stack
Built on production-grade tools.
Automation Layer
n8nMakeCustom Node
AI Layer
ClaudeGPT-4
Data
SnowflakeBigQueryPostgres
Sources
StripeHubSpotGA4
Notification
SlackGmail
Stack varies based on your existing tools — we work with what you have.
Variations
Other ways we build this.
Lite
Single source, single channel. Good for early-stage teams.
Standard
Multi-source, AI commentary, multi-channel delivery.
Enterprise
Multi-team customised reports with anomaly escalation.
Related use cases
Often built alongside this.
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PDF invoices and receipts parsed, validated, matched to POs, routed to approvers, and synced to your
View use caseCustomer Support Triage
Inbound tickets categorised, prioritised, pre-drafted with cited KB snippets, and routed to the righ
View use caseGet started
Stop losing time. Start tomorrow.
Book a free 30-minute call. We'll map your current process and show you exactly what we'd automate first.