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ai · 1 min read

Browser-Using Agents: Letting AI Drive Real Web Apps

Browser-using agents unlock automation for systems with no API. Here is how Bhogar AI runs them safely at scale, with sandboxing and human-in-the-loop fallbacks.

BABhogar AI TeamProduct & Engineering

There is a long tail of business systems with no public API. Browser-using agents - LLMs that drive a real browser - finally unlock automation for that long tail without building a custom integration.

Why it matters

The risks are real: a misbehaving browser agent can submit forms, send emails, or buy things. Production deployment requires sandboxing, human approval gates and recordable sessions for audit.

How Bhogar AI approaches it

Bhogar AI runs browser agents in ephemeral, network-isolated containers with a supervisor that can pause, replay and approve actions. Every click and keystroke is recorded, every credential is fetched from the secret manager just-in-time, and every session is bounded by a hard time and cost budget.

  • Ephemeral isolated browser sandboxes with no persistent state
  • Human-in-the-loop approval for risky action classes
  • Full session replay for audit and debugging
  • Credential injection from your existing secret manager
  • OWASP-aligned defences against prompt injection from page content

What you get

Operations teams replace 30-50 hours/month of manual data entry per analyst with browser agents, with measurable accuracy gains versus copy-paste workflows.

See Bhogar on your own data

Book a 45-minute working session. We connect one of your sources, build one agent, run one governed workflow, and review the trace together.