What tech stack does ElevenLabs use?

ElevenLabs's backend is Python-first, consistent with every major AI voice company at production scale. Job postings consistently require Python, Kubernetes, and cloud infrastructure experience. PyTorch is the primary deep learning framework for model training — the industry standard for neural TTS — with inference serving managed on Google Kubernetes Engine (GKE).

Google Cloud Platform is ElevenLabs's primary and publicly confirmed cloud provider following a multi-year strategic partnership announced in February 2026. The partnership provides access to GCP G4 virtual machines powered by NVIDIA RTX PRO 6000 Blackwell GPUs, chosen specifically for training and serving ElevenLabs's voice models at the sub-200ms latency required for real-time agents. ElevenLabs implemented GPU optimization strategies on GKE including multi-instance GPUs and time-sharing to improve utilization and reduce per-inference cost. In May 2026, Google Cloud named ElevenLabs its 2026 Applied AI Partner of the Year, recognizing measurable customer success and technical innovation on GCP.

For enterprise VPC deployments where customers run ElevenLabs models inside their own cloud environments, the company supports both AWS SageMaker and Google Cloud Vertex AI. The ElevenLabs product integration with Google Gemini (embedded into ElevenAgents for multi-step reasoning and planning in voice interactions) and Google Veo (embedded into ElevenCreative for AI-generated video and audio content) further deepens the GCP platform integration beyond raw compute.

ElevenLabs's frontend is built in React and TypeScript, reflected in its open-source SDK and UI component library available at github.com/elevenlabs/packages. The publicly available TypeScript Agent SDK powers the ElevenAgents developer experience and is the primary integration surface for developers building voice agents. The public-facing web application uses Next.js, confirmed by the company's own engineering blog and consistent with Stripe's published customer integration materials. WebSocket streaming is the core data transport for real-time voice inference, enabling the low-latency bidirectional audio streams that ElevenAgents relies on for conversational use cases.

For GTM tooling, ElevenLabs has confirmed native HubSpot and Salesforce integrations as part of ElevenAgents' out-of-the-box enterprise connectors. HubSpot webhooks allow ElevenLabs voice agents to read and write CRM records in real-time during customer calls, enabling agents to update contact records, log call outcomes, and trigger follow-up workflows automatically. Salesforce is both a strategic investor (Series D third close, May 2026) and a confirmed integration partner, and is almost certainly used internally by ElevenLabs's own enterprise sales team given the company's 20x ACV expansion motion and the Salesforce investor relationship.

Stripe is confirmed as ElevenLabs's payment processor based on published customer integration references and the company's own developer documentation. The pnpm and Turbo toolchain, visible in public GitHub repositories, is used for the TypeScript SDK monorepo management.

ElevenLabs is a Google Cloud-committed customer with a public multi-year GCP partnership, GKE as the confirmed inference orchestration layer, and NVIDIA Blackwell GPUs as the confirmed training hardware. Vendors in the GCP ecosystem — cloud security, GKE monitoring, FinOps, MLOps, and AI observability — have a structural entry point through the shared GCP platform relationship. NVIDIA's NVentures investment in the May 2026 Series D further signals deep hardware alignment and opens the door for NVIDIA-ecosystem vendors.

At 600+ employees and $500M ARR, ElevenLabs has crossed the scale threshold where it buys enterprise-grade solutions for observability, security, data infrastructure, and developer productivity rather than building everything in-house. The Python + PyTorch + GKE stack is conventional for a high-growth AI company at this stage, and typical enterprise tooling needs at this scale include ML experiment tracking (MLflow, Weights & Biases), LLM observability (Arize, Langfuse), infrastructure security (Wiz, Orca), and data pipeline tooling (dbt, Fivetran).

The confirmed HubSpot and Salesforce integrations confirm a sales-led enterprise motion with a CRM-first workflow. Sales engagement platforms (Outreach, Salesloft, Apollo), revenue intelligence tools (Gong, Chorus), and sales forecasting tools (Clari) are the most likely adjacent stack purchases as the enterprise GTM team scales through the Series D deployment. Sellers in those categories should target Carles Reina's VP Revenue organization as the primary buyer, and can use the Gemini and Salesforce investor relationships as warm referral angles.