Kameleo is a developer-focused SaaS company building an antidetect browser that integrates with Selenium, Puppeteer, and Playwright. Their customers are advanced engineering teams that rely on Kameleo to bypass anti-bot systems and extract data at scale. The company manages continuous product updates, evolving documentation, and a steady flow of deeply technical customer questions.
But as their customer base grew, their documentation fell out of sync, engineers struggled to keep pace with updates, and customers waited for answers that could only be delivered during human support shifts. The team needed a faster, more reliable way to respond, update knowledge, and reduce manual load.
Helply became the turning point. What started as a simple experiment became a complete upgrade to Kameleo’s support workflow and knowledge operations.
Key Performance Highlights
78% Resolution rates
Kameleo is now resolving more than 75% of all customer inquiries monthly automatically with Helply.
3x faster support response times
The team expanded beyond forms and tickets and now delivers real-time replies around the clock.
2x customer engagement
Customers now ask more questions, get answers faster, and engage directly with Helply for code generation and troubleshooting.
The Moment Everything Became Unsustainable
Before Helply, Kameleo relied on a Zendesk knowledge base and GitHub examples, maintained manually by the technical support engineering team. Every update required engineers to rewrite documentation. More importantly, leadership had no reliable way to track what was updated, what was missing, or where customers were getting stuck.
This resulted in:
- documentation drift
- repetitive support questions
- limited visibility
- support hours constrained by human shifts
Tamas Deak, CEO of Kameleo, described the strain clearly.
“We had a lack of control over what was updated or what needed updating. Helply gave me visibility and ensured we weren’t wasting time.”
Kameleo’s customers are highly technical. They write code. They integrate with automation frameworks. When they hit a blocker, they expect answers fast. But Kameleo had no chat system and could only respond through Zendesk during engineer hours. The mismatch became obvious.
The Turning Point
Tamas discovered Helply almost by accident. While on a flight, he opened LinkedIn and saw a friend comment on a post from Alex Turnbull. It was a one-page breakdown of a PLG strategy. He downloaded it, read it offline for the rest of the flight, and realized instantly:
“This is a perfect match for us.”
Kameleo met the VIP program access criteria. It was the start of a new quarter. Tamas wanted to introduce AI. The timing aligned perfectly. He reached out, joined the program, and began the integration.
Why Helply Was Different
Tamas had already experimented with AI support. He connected Zendesk to ChatGPT 3.5 months earlier.
The limitation was obvious.
AI could answer questions, but it could not measure coverage, identify gaps, or ensure documentation stayed aligned with what customers actually needed.
Helply delivered something much deeper.
- real-time knowledge gap detection
- auto-generated insight reports
- ability to measure engineer performance without micromanaging
- clear visibility into what customers search for and ask
- code generation directly from Kameleo’s own knowledge
- AI that behaves like frontline support rather than a generic chatbot
“The thing is, Helply is more than an AI bot. It’s a platform that helps you track things. Gap Finder showed us our true coverage. That helped me see exactly what needed to be added.”
How Kameleo Uses Helply Today
Helply is now Kameleo’s frontline support.
More conversations come through Helply than through Zendesk forms.
Every day, the team updates Helply and tunes escalation paths to continuously reduce tickets. Tamas is still experimenting with whether to update Zendesk or Helply first, but the outcome is the same:
- Customers get answers instantly.
- The support team has more time.
- Escalations drop.
Their users now ask far more technical questions because they know Helply can answer them. Many questions are code generation requests:
“Generate the integration code for my setup.”
Helply reads their knowledge base and returns exactly what the customer needs.
This alone saves the technical support team hours each day.
The Results
- 78% resolution rates, consistently.
- Customers now engage more, get answers faster, and trust the AI Agent immediately.
- Engineers save time by not rewriting repetitive code examples.
- They can focus on deeper technical work.
- Documentation accuracy is now measurable.
- Gap Finder revealed that Kameleo’s documentation was only 70% complete and Helply showed exactly where to fill the gaps.
- Response times improved dramatically.
- No more waiting for engineers’ shifts.
- Users consistently share positive feedback.
- Many mention that Helply already answered their question before escalating.
“Some people are lazy and just want quick answers. Others are deeply technical. Helply serves both. And they’re surprised that the AI actually answers their questions.”
Secondary Impact
Helply changed how Kameleo thinks about documentation entirely.
Instead of engineers manually guessing what needs to be updated, Tamas now uses reports to direct improvements with precision.
This shift turned documentation from a guessing game into a measurable system.
Kameleo also discovered which knowledge lives best in Helply versus Zendesk, opening the door to a more flexible documentation strategy.
The Future
Kameleo plans to deepen their integration and continue reducing escalation rates. Helply’s analytics will guide which content gets updated, rewritten, or replaced entirely. The team expects to expand their self-service footprint as Helply becomes the first place customers go to solve problems.
Final Word
“Every AI tool gives impact. The question is how hard it is to integrate. With Helply, the integration was effortless with the VIP program.”
