The Business Challenge
The business situation the organisation faced before the project began.
Marketing agencies relied on manual website contact form submissions for outbound prospecting. Teams spent significant time locating valid forms, entering repetitive information, and tracking campaign performance. The process was difficult to scale, prone to human error, and frequently interrupted by anti-bot protections, limiting both productivity and outreach volume.
How the Solution Was Delivered
Discovery, design, development, testing and rollout — the journey, not the tooling.
- 1Gathered outreach workflow requirements and analyzed manual bottlenecks.
- 2Built a scalable URL validation pipeline using distributed headless browsers.
- 3Implemented AI-powered contact form detection and intelligent field mapping.
- 4Integrated browser automation with proxy rotation and stealth submission techniques.
- 5Developed asynchronous processing queues with per-domain rate limiting.
- 6Added real-time campaign tracking and automated message variant optimization.
- 7Optimized proxy health, submission success detection, and campaign performance for production deployment.
Business Outcomes & Impact
The measurable outcomes recorded on this AI Case Study — with the story behind them.
Increased outreach capacity from approximately 50 manual submissions per day to thousands of automated submissions daily, reduced manual outreach effort by around 80%, and achieved an average 78% successful submission rate across validated website contact forms.
Business Outcome Categories
The story behind the numbers
Increased outreach capacity from approximately 50 manual submissions per day to thousands of automated submissions daily.
Reduced manual outreach effort by roughly 80%.
Achieved approximately 78% successful submission rate across validated contact forms.
Enabled continuous campaign optimization using real-time reply and conversion tracking.
Significantly improved scalability while reducing repetitive manual work.
Lessons Learned
What surprised the team, what worked well, and what would be done differently.
- Reliable automation depends as much on infrastructure as AI models.
- Continuous feedback loops produce better long-term campaign performance than static automation.
- Proxy health and browser fingerprint management are critical for large-scale web automation.
- LLMs significantly improve form understanding compared to rule-based approaches.
- Operational monitoring is essential for maintaining production AI systems at scale.