Build once, run forever.
Compile intent into code. Run it everywhere.
The architecture in one picture.
Three phases. One platform.
Planning time
Domain expertise applied to your business.
Mark learns your product, ICP, competitive landscape, and then proposes a prioritized GTM plan. You review and adjust it. Once it's approved, Airtop builds agents to execute it.
The four pillars
The performance gap is not subtle
Same task. Same target. 99% cheaper.
A standard lead generation task: find LinkedIn engagement on a target post, enrich the people who engaged, qualify them against an ICP, and push the qualified ones to outreach.
That is roughly 99x cheaper and 6x faster than Claude Code on Opus, and 48x cheaper and 13x faster than Sonnet. The gap widens as volume grows: an LLM-in-the-loop agent's cost is linear in steps and runs, while a code-first agent's cost is dominated by infrastructure.
Universal reach
Any API. Any website.
Most automation platforms cover the slice of the world that has a clean API. Airtop covers the rest as well.
APIs
Public web
Authenticated web
Adversarial web
Legacy and vendor portals
Native HTTP, OAuth, webhooks, and structured tool calls
Static and dynamic pages, JavaScript-rendered apps, infinite scroll
Sites behind logins, 2FA, and SSO, with credentials vaulted per workspace
CAPTCHA solving, anti-bot evasion, residential proxies
Click-through workflows for software that was never meant to be automated
This is why Airtop agents work on LinkedIn, government sites, vendor portals, internal tools, and the dozens of consumer and B2B services that have no usable API.
Vertical agents on top of the platform
One platform. Many products.
(More agents coming soon)
Built for production from day one
The boring properties that decide whether you can put an agent in front of customers.
- SOC 2 Type II and HIPAA compliant
- Encrypted credential storage, isolated per workspace
- Customer data is never used to train any model, ours or anyone else's
- Full audit trail for every run: actions, data, video replay
- Role-based access, SSO, and granular permissions
- Cloud isolation per agent
Why this matters now
AI agents are moving from demo to deployed.
The first wave of agent platforms optimized for impressive demos. The second wave has to optimize for reliability, cost, and reach, because that is what the move from one user to one thousand users requires. Code-first agents are not an incremental improvement on LLM-in-the-loop agents. They are a different architecture, with a different cost curve and a different reliability ceiling.
Teams that adopt this architecture now will compound a structural advantage over teams still stitching prompt chains.
See it run.
Spin up your first agent in five minutes.