Scaling AI adoption across product, analytics,
and engineering with Claude

Industry:

Enterprise SaaS

Headquarters:

Herndon, Virginia

Founded in:

2000

Company Size:

201 - 500 employees

Featured Tags:

Overview

FranConnect is a franchise management SaaS provider that helps businesses manage franchise operations, customer relationships, reporting, and growth. As the volume of customer, product, and operational data increased, teams needed faster ways to turn unstructured information into actionable insight.

FranConnect began embedding Claude across its AWS environment to bring AI into customer-facing applications, internal analytics, operational monitoring, and software development. Using Claude through Amazon Bedrock, alongside Claude Code and Claude Enterprise, the company moved AI beyond experimentation into production use cases across the organization.

Challenges

FranConnect was generating more data and information than teams could efficiently interpret, creating bottlenecks across both product and internal operations:

Long customer contracts required manual review and summarization.
Raw reporting data needed significant interpretation before reaching stakeholders.
Product usage data contained behavioral signals buried in high-volume S3 data.
Operational logs required continuous analysis to identify meaningful patterns.
AI-assisted development needed greater visibility into adoption and contributions.

FranConnect needed a scalable approach to embed AI into existing workflows while maintaining control over its AWS environment, data, and engineering processes.

The Solution

Solution:

CloudKeeper worked with FranConnect to identify and evaluate AI use cases across customer-facing applications, analytics, operations, and engineering, with a focus on moving high-value workloads from experimentation into production.

Customer-Facing Contract Intelligence

Integrated Claude through Amazon Bedrock into FranConnect's production application.
Enabled automated summarization of PDF-based customer contracts.
Brought AI-generated contract insights directly into the customer experience.
Successfully moved contract summarization into production.

AI-Powered Analytics

Used Claude to transform raw reporting outputs into polished summaries and actionable narratives.
Analyzed login and usage data stored in Amazon S3 to identify behavioral patterns and engagement signals.
Applied AI to reduce the manual interpretation required across reporting and customer analytics.

Intelligent Operational Monitoring

Augmented ELK/OpenSearch logs with AI-generated monitoring insights.
Used Claude to surface operational anomalies, trends, and meaningful signals from large volumes of log data.
Reduced Mean Time to Detect (MTTD) by 70%.
Reduced alert noise by 75%.

AI-Assisted Engineering

Deployed Claude Code and Claude subscriptions across the engineering organization.
Enabled AI-assisted coding, code review, and software delivery workflows.
Achieved approximately 8 hours of time savings per engineer per week.
Expanded AI adoption beyond individual experimentation into organization-wide engineering workflows.

Scaling AI Architecture

As FranConnect evaluated scaling its chatbot to 300,000–400,000 documents within a multi-tenant architecture, CloudKeeper supported the vector store evaluation.

Modeled OpenSearch Serverless against Amazon S3 Vectors across capacity, re-indexing costs, and latency.
Validated sizing assumptions against the expected document scale.
Helped inform the architecture decision for the next stage of AI workload growth.

FranConnect also adopted a model-per-task approach, using Claude 3 Haiku, Claude Haiku 4.5, Claude Sonnet 4.5, Claude Sonnet 4.6, and Claude Opus 4.5 based on workload requirements rather than applying a single model across every use case.

Impact

CloudKeeper helped FranConnect establish a broader foundation for AI adoption across its product and engineering ecosystem.

Metrics	Outcomes
AI Use-Case Families	5 use-case families running or under evaluation.
Contract Summarization	Production-grade, customer-facing capability.
MTTD	70% reduction.
Alert Noise	75% reduction.
Engineering Productivity	~8 hours saved per engineer per week.
AI Adoption	Organization-wide Claude Code and subscription deployment.
AI Architecture	Vector store architecture evaluated for 300K–400K documents.

Outcomes

Production AI embedded in customer workflows.

Faster interpretation of operational and product data.

Significant reduction in monitoring noise.

Faster engineering workflows across the organization.

Scalable foundation for expanding AI use cases.

Conclusion

FranConnect's work with CloudKeeper demonstrates how AI can move from isolated experimentation to an operational capability embedded across the technology stack. By integrating Claude through Amazon Bedrock and extending AI into analytics, monitoring, customer applications, and engineering workflows, FranConnect has established multiple practical paths for AI adoption.

With five use-case families running or under evaluation, a production customer-facing AI capability, measurable improvements in operational monitoring, and organization-wide engineering adoption, FranConnect now has a scalable foundation for expanding AI across its product and operations.

Talk to our team