Deepgram today announced the general availability (GA) of its Voice Agent API, a single, unified voice-to-voice interface that gives developers full control to build context-aware voice agents that power natural, responsive conversations. Combining speech-to-text, text-to-speech, and large language model (LLM) orchestration with contextualized conversational logic into a unified architecture, the Voice Agent API gives developers the choice of using Deepgram’s fully integrated stack (leveraging industry-leading Nova-3 STT and Aura-2 TTS models) or bringing their own LLM and TTS models. It delivers the simplicity developers love and the controllability enterprises need to deploy real-time, intelligent voice agents at scale. Today, companies like Aircall, Jack in the Box, StreamIt, and OpenPhone are building voice agents with Deepgram to save costs, reduce wait times, and increase customer loyalty.
In today’s market, teams building voice agents are often forced to choose between two extremes: rigid, low-code platforms that lack customization, or DIY toolchains that require stitching together STT, TTS, and LLMs with significant engineering effort. Deepgram’s Voice Agent API eliminates this tradeoff by providing a unified API that simplifies development without sacrificing control. Developers can build faster with less complexity, while enterprises retain full control over orchestration, deployment, and model behavior, without compromising on performance or reliability.
Developer Simplicity and Faster Time to Market
For teams taking the DIY route, the challenge isn’t just connecting models but also building and operating the entire runtime layer that makes real-time conversations work. Teams must manage live audio streaming, accurately detect when a user has finished speaking, coordinate model responses, handle mid-sentence interruptions, and maintain a natural conversational cadence. While some platforms offer partial orchestration features, most APIs do not provide a fully integrated runtime. As a result, developers are often left to manage streaming, session state, and coordination logic across fragmented services, which adds complexity and delays time to production.
Deepgram’s Voice Agent API removes this burden by providing a single, unified API that integrates speech-to-text, LLM reasoning, and text-to-speech with built-in support for real-time conversational dynamics. Capabilities such as barge-in handling and turn-taking prediction are model-driven and managed natively within the platform. This eliminates the need to stitch together multiple vendors or maintain custom orchestration, enabling faster prototyping, reduced complexity, and more time focused on building high-quality experiences.
In addition to the Voice Agent API, organizations seeking broader integrations can leverage Deepgram’s extensive partner ecosystem, including Kore.ai, OneReach.ai, Twilio and others, to access comprehensive conversational AI solutions and services powered by Deepgram APIs.
Maximum Control and Flexibility
While the Voice Agent API streamlines development, it also gives teams deep control over performance, behavior, and scalability in production. Built on Deepgram’s Enterprise Runtime and full model ownership across the entire voice AI stack, the platform enables model-level optimization at every layer of the interaction loop. This allows for precise tuning of latency, barge-in handling, turn-taking, and domain-specific behavior in ways not possible with disconnected components.
Key capabilities include:
- Flexible Deployment: Run the complete voice stack in cloud, VPC, or on-prem environments to meet enterprise requirements for security, compliance, and performance.
- Runtime-Level Orchestration: Deepgram’s runtime supports mid-session control, real-time prompt updates, model switching, and event-driven signaling to adapt agent behavior dynamically.
- Bring-Your-Own Models: Teams can integrate their own LLMs or TTS systems while retaining Deepgram’s orchestration, streaming pipeline, and real-time responsiveness.
This tightly coordinated design translates directly into measurable performance gains. In recent benchmark testing using the Voice Agent Quality Index (VAQI), Deepgram achieved the highest overall score among all evaluated providers (see Figure 1). VAQI is a composite benchmark that measures the core elements of voice agent quality: latency (how quickly the agent responds), interruption rate (how often it cuts users off), and response coverage (how often it misses valid input).
Deepgram outperformed OpenAI by 6.4% and ElevenLabs by 29.3%, reflecting the advantage of its integrated architecture and model-driven turn-taking. The result is smooth, responsive conversations without missed inputs, premature responses, or unnatural delays.
Cost-Effectiveness at Scale
In addition to control and performance, the Voice Agent API is built for cost efficiency across large-scale deployments. When teams run entirely on Deepgram’s vertically integrated stack, pricing is fully consolidated at a flat rate of $4.50 per hour (see Figure 2). This provides predictable, all-in-one billing that simplifies planning and scales with usage. Deepgram’s vertically integrated runtime also delivers unmatched compute efficiency, optimizing every stage of the speech pipeline to minimize infrastructure costs while maintaining real-time responsiveness.
For teams that bring their own LLM or TTS models, Deepgram offers built-in rate reductions, enabling even lower total cost of ownership for production-scale deployments.
Start Building with the Voice Agent API
Experience how fast and flexible voice agents can be with Deepgram’s unified voice-to-voice API. Explore the API in our interactive playground, review documentation, or integrate in minutes using our SDK. New users receive $200 in free credits, enough to process over 40 hours of real-time voice agent usage. Start building natural, responsive conversations with infrastructure built for real-time performance and enterprise-scale.
Additional Resources:
- Explore the blog for an in-depth breakdown of Voice Agent API’s capabilities
- Watch a fun demo of Deepgram’s voice agent API
- Try Deepgram’s interactive demo
- Get $200 in free credits and try Deepgram for yourself
Westjet Pwned In An Ongoing Cyberattack
Posted in Commentary with tags Hacked on June 16, 2025 by itnerdCanada’s number 2 airline Westjet is apparently dealing with a cyberattack. Bleeping Computer has the details:
“WestJet is aware of a cybersecurity incident involving internal systems and the WestJet app, which has restricted access for several users,” reads a security advisory on WestJet’s site.
“We have activated specialized internal teams in cooperation with law enforcement and Transport Canada to investigate the matter and limit impacts.”
“We are expediting efforts to maintain the safety of our operation and safeguard sensitive data and personal information for both our guests and employees, and we apologize to all guests for any disruption to their access to WestJet’s services.”
The attack also prevented users from logging into the website and mobile app, with those services now restored.
Christian Geyer, founder and CEO of Actfore had this to say:
“In a cyberattack like the one affecting WestJet, time is everything. The ability to rapidly identify what was stolen, and who’s behind it, can make or break the company’s response. This is why aviation and critical infrastructure companies need a battle-tested response plan, with pre-identified trusted partners in the response.”
It will be interesting to see what Westjet says in regards to all of that. Because as I type this, Westjet has not given a whole lot of detail. But they will need to if anyone will trust them again.
Leave a comment »