Oya
Getoya provides a runtime platform for building and operating AI agents that perform real work for businesses, such as SDR, support, and marketing roles. The platform uses a deterministic runtime that executes typed plans, reducing token usage by 4.7x and ensuring critical values are preserved. It includes Oya Browser, which lets agents record successful browser tasks as playbooks and replay them with new inputs.
- AI Agents
- Artificial Intelligence
- Enterprise Software
- Software Only
- Developer Tools
Funding
Founders
Founder details are not available yet.
Product
Problem
Most AI agents are non-deterministic prompt wrappers around an LLM, leading to silent state corruption, ordering drift, and excessive token costs in production. These failures—where critical values are altered or steps run out of sequence—make agents unreliable for real operational work and difficult to audit.
Solution
OyaAI is a runtime platform for OAgents, which are agents a business runs for someone else, like an SDR or support agent. The platform uses a planner that emits a typed plan, which a deterministic runtime executes, passing values by reference so the model only reads what it needs. This architecture keeps roughly 80% of compute deterministic, reducing token usage by ~4.7x and ensuring critical values are preserved byte-for-byte. Every run is fully recorded and replayable, providing a complete trace of actions for auditability and customer accountability. The platform also includes Oya Browser, which lets agents operate a browser, record successful tasks as playbooks, and replay them with new inputs.
Target Audience
Primary customers are businesses that deploy AI agents on behalf of their own customers, such as sales development, customer support, and onboarding teams, who need reliable, auditable, and cost-effective automation. The platform also serves founders, small teams, agencies, and growth teams that need virtual employees for marketing, sales, and operations.
Features
- Deterministic runtime that executes a typed dataflow plan, preventing state corruption and ordering drift
- Skills are versioned, sandboxed Python integrations with typed input/output schemas, reusable across agents
- Secrets and sensitive data are kept in the deterministic layer, never reaching the model, preventing prompt injection
- Full execution trace, including LLM calls, tool calls, and sandbox output, is recorded and replayable step-by-step
- One agent identity works across multiple channels, including web chat, Slack, Telegram, webhooks, and scheduled jobs
- Benchmarks show ~4.7x fewer LLM tokens per task and 100% critical value preservation versus ReAct loops
- Oya Browser provides a record-replay-refine workflow where successful browser tasks are saved as playbooks and replayed as code without fresh AI planning
- Pre-built templates for 10 roles (SDR, LinkedIn manager, SEO) and 60+ production-ready skills with 20+ managed integrations