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Our QA flow agent caught 847 bugs last month. Our Ingage agent sent 12,000 personalized LinkedIn messages. Our Shoreline agent updated 340 contracts automatically.
None of this required human intervention.
These aren't hypothetical use cases. They're production systems running right now across our portfolio. Here are five AI agents that are actually working in 2025-and what they're teaching us about the future of software.
1. QA testing agents (QA flow)
What it does: Runs comprehensive test suites 24/7, detects bugs, proposes fixes, and deploys solutions autonomously.
The impact: One Series B client reduced their QA cycle from 2 weeks to 3 days. Their engineering team now ships features 5x faster.
The lesson: Testing isn't just automatable-it's improvable. Our agent learns from every bug it finds, improving test coverage without human direction.
2. Sales engagement agents (Ingage)
What it does: Monitors LinkedIn for high-intent prospects, engages with their content, sends personalized messages, and syncs everything to your CRM.
The impact: A B2B SaaS client generated 40 qualified leads in their first month. Their sales team stopped cold outreach entirely.
The lesson: Authenticity scales when AI understands context. Our agent doesn't spam-it engages genuinely based on prospect behavior.
3. Compliance monitoring agents (Shoreline EOR)
What it does: Tracks regulatory changes across Canadian provinces, identifies impact on client agreements, updates contracts automatically, and notifies stakeholders.
The impact: What used to require three full-time compliance analysts now runs autonomously. Zero compliance violations in 8 months.
The lesson: Regulatory work is perfect for AI agents-high stakes, low tolerance for error, constant change.
4. Customer onboarding agents
What it does: Guides new users through product setup, answers questions in real-time, identifies blockers, and escalates complex issues to humans.
The impact: One client reduced time-to-value from 14 days to 2 days. Activation rates jumped 60%.
The lesson: AI agents excel at repetitive processes that require judgment. They never tire of explaining the same feature twice.
5. Data validation agents
What it does: Monitors data quality across systems, flags anomalies, attempts auto-correction, and maintains audit trails.
The impact: A fintech client eliminated 90% of data quality issues before they reached production.
The lesson: Prevention beats detection. Agents catch problems before humans notice them.
The pattern across all five
Notice the commonality: these aren't AI assistants waiting for prompts. They're autonomous systems that perceive, reason, act, and learn.
They operate in the background. They never sleep. They get better over time.
What to build first
Start with the workflow that's both high-volume and rule-based. Customer onboarding is ideal-lots of repetition, clear success criteria, immediate impact.
Don't try to automate everything at once. Pick one agent. Build it. Learn from it. Then scale.
The companies winning with AI agents aren't the ones with the best models. They're the ones who started building six months ago.
Want to build AI agents for your product? Learn more about Islands
Want to learn more?
Let’s talk about what you’re building and see how we can help.
No pitches, no hard sell. Just a real conversation.
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You’re all set!
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