Company Profile
Company Type
B2B SaaS platform
Team Size
30-120 employees
Industry
SaaS
Key Challenge
Struggling with inefficient manual follow-up processes that were slowing growth and increasing operational costs. Their primary concern was onboarding speed.
Tools Connected
The Challenge
Manual follow-up was the biggest bottleneck in this b2b saas platform's operations. Their team of 30-120 employees processed hundreds of follow-up requests weekly, each requiring multiple steps, cross-referencing against saas-specific requirements, and coordination between departments. The average follow-up request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.
Beyond the time drain, the quality of their follow-up output was inconsistent. Different team members followed different procedures, and there was no standardized way to handle edge cases that are common in saas. A recent audit revealed that 12% of completed follow-up records contained errors that required rework — costing the organization an additional $50K annually in correction and remediation efforts. The leadership team recognized that continuing to throw people at the problem wasn't viable and began searching for an AI-powered solution.
The Solution
Arahi AI provided the automation backbone this saas team needed. They deployed a multi-agent workflow that breaks the follow-up process into discrete, automated steps — each handled by a specialized AI agent. The first agent monitors triggers from HubSpot and Slack. The second agent analyzes and processes incoming requests using saas-specific business logic. The third agent executes actions across connected tools and notifies team members via Notion.
The beauty of the no-code approach was speed of implementation. The team had their first agent live within 90 minutes, and the full follow-up workflow was operational within a single afternoon. They used Arahi AI's template for saas follow-up as a starting point, customized the business rules to match their specific process, and connected their existing tool stack without writing a single line of code. Within the first week, the agents had processed over 200 follow-up instances with high accuracy — more than the team typically handled in a month.
The Results
Measurable improvements across key saas follow-up metrics.
Task Completion Time
Dramatically faster
Before
Hours
After
Minutes
Team Productivity
Significant increase
Before
Baseline
After
Multiplied output
Quality Score
Notable improvement
Before
Inconsistent
After
Consistently high
Monthly Cost
Major savings
Before
High
After
Much lower
Customer Satisfaction
Notable increase
Before
Below target
After
Above target
“We went from spending half our day on follow-up to having it just happen automatically. The AI agents handle the routine work perfectly, and our saas team can focus on the strategic decisions that actually move the needle. I wish we had done this a year ago.”
VP of Operations
B2B SaaS platform
Key Takeaways
The most important lessons from this saas follow-up automation project.
This saas team proved that follow-up automation doesn't require technical expertise — the no-code platform made it accessible to business users.
Scaling follow-up capacity dramatically without adding headcount fundamentally changed the economics of their saas operations.
Consistent AI-powered processing eliminated the quality variance that came with different team members handling follow-up differently.
Real-time visibility into follow-up metrics gave leadership the data they needed to make better strategic decisions.
Implementation Timeline
From zero to production in 90 minutes — here's how they did it.
Step 1: Mapped the existing follow-up workflow
Documented every step of the current manual follow-up process, including decision points, exceptions, and handoffs between team members. Identified which steps could be fully automated versus those needing human oversight.
Step 2: Built the automation in Arahi AI
Used Arahi AI's no-code builder to create the follow-up workflow: connected HubSpot and Stripe as data sources, configured AI decision logic for saas-specific requirements, and set up automated actions and notifications.
Step 3: Parallel run with manual process
Ran the AI agents alongside the manual process for one week to compare outputs. The AI matched or exceeded human accuracy on the vast majority of follow-up instances, with edge cases automatically flagged for human review.
Setup Time
90 minutes
AI Agents
4 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating follow-up in saas.
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This case study represents a typical customer scenario. Individual results may vary.