Blog archive
417 Dasha articles about voice AI, conversational AI, and building production-ready agents.
2026
- Six Voice AI Implementation Examples for Sales Teams
Voice AI case studies often headline an outcome while omitting the machinery that produced it. Implementation teams need the call trigger, data contract, conversation boundary, tool actions, escalation path, and measurement plan. We build Dasha for that production layer. These implementation…
- Voice activity detection: From audio frames to natural turns
Voice activity detection looks simple: label each audio frame as speech or non-speech. In a live voice agent, that decision controls whether a caller's first syllable survives, when the agent responds, and whether background noise triggers an interruption. Understanding the path from raw frames to…
- AI Agent Security: A Practical Architecture Guide
An AI agent can turn one bad model response into an account change, message, booking, or API call. That makes agent security an architecture problem for any team giving models tools, memory, or access to business data. We build and run production voice AI agents at Dasha, where a spoken turn can…
- OpenAI Realtime API: A practical guide for voice agents
The OpenAI Realtime API puts live audio, model reasoning, and spoken responses in one stateful session. That can shorten the voice path, but a working demo still leaves important architecture decisions to your team. Here is how the current API works, which transport to use, what it costs, and what…
- Bring your own carrier (BYOC): architecture, tradeoffs, and rollout
Moving a phone operation to the cloud often exposes a hidden dependency: the software platform also wants to become the telecom provider. Bring Your Own Carrier (BYOC) separates those decisions. That separation can preserve numbers, contracts, routing, and regional coverage, but it also leaves your…
- SIP Trunking Explained: Architecture, Setup, and Production Testing
SIP trunking looks simple on a network diagram. Production failures tend to hide in the details: signaling succeeds while audio fails, a codec mismatch rejects calls, or a campaign exceeds the carrier's call-rate limit. A sound design treats routing, media, security, capacity, and recovery as…
- White-label AI voice agent platforms: 5 options and how to choose
A white-label AI voice agent can put your brand in front of clients within days. The harder question is what sits behind that brand. Your choice determines who owns the customer experience, runtime, data, billing, support, and migration risk. The right platform depends on whether you are packaging…
- The voice AI stack: a practical seven-layer model
A voice agent can sound convincing in a demo and still fail on a live phone line. The difference is usually in the stack around the model: audio transport, turn detection, state, tools, cancellation, and the evidence your team gets when something goes wrong. A useful architecture therefore starts…
- 25 missed call message templates that make the next step clear
A missed call leaves both sides guessing. The caller does not know whether anyone noticed, and the recipient does not know why they called. A clear message closes that gap. For businesses with recurring call volume, we help technical teams build inbound voice agents that answer, qualify, and route…
- Voice Agent Evaluation: Metrics, Scorecards, and Release Gates
A voice agent can say the right words and still make the wrong change. It can also complete the task while giving the caller a slow, confusing experience. Voice agent evaluation turns call evidence into scores and release gates. A sound framework keeps outcomes, speech quality, timing, safety, and…
- Speech-to-text pricing for production voice AI
Published production streaming speech-to-text prices compared here start at $0.15 per hour. OpenAI lists an estimated live-transcription cost of $0.017 per minute, equal to $1.02 per hour at that estimate. Session billing, silence, channels, diarization, language features, minimums, retries,…
- 7 Best Vapi Alternatives for Production Voice AI in 2026
The best Vapi alternative depends on which part of Vapi you want to replace.
- AI Telemarketing: How to Build a Production Campaign
AI telemarketing uses software to prepare, place, handle, and evaluate sales calls. A conversational voice agent can contact permitted leads, ask approved qualification questions, answer bounded product questions, schedule a next step, update a customer relationship management (CRM) system, and…
- Voice Agent Testing: An End-to-End Guide for Technical Teams
Voice agent testing verifies that an agent can complete real tasks across text, browser audio, and phone calls before and after release. A reliable plan covers business rules, multi-turn conversations, tool calls, speech, turn-taking, interruptions, failures, transfers, and rollback. This guide…
- 7 Best AI Voice APIs for Developers in 2026
There is no single best voice AI API for every product. The right choice depends on which layers you want a vendor to run. We recommend Dasha for technical teams that want a managed production runtime with API control. Vapi is strong for hosted provider flexibility, Retell AI for integrated phone…
- What Is an AI Agent Runtime? Architecture and Platform Guide
An AI agent runtime is the execution layer that turns an agent definition into a running process. It manages the model-and-tool loop, session and workflow state, permissions, interruptions, failures, streaming, and telemetry. Some products also bundle hosting, long-term memory, sandboxes,…
- Best Enterprise Voice AI Platforms in 2026: 8 Compared
The right enterprise voice AI platform depends on the operating responsibilities your team can support. Dasha offers a managed runtime with APIs, Session Initiation Protocol (SIP), provider choice, and public usage pricing. Retell AI emphasizes integrated testing and live supervision; Vapi…
- 10 best AI voice agent platforms for production teams in 2026
Choosing the best AI voice agent platform comes down to what you want to build, how much of the stack you want to control, and how much production infrastructure your team is prepared to own. A polished demo is easy. Reliable telephony, interruption handling, tool calls, monitoring, failover, and…
- AI voice agent pricing: a practical guide to total cost
AI voice agent pricing in the self-serve examples reviewed here starts with advertised base rates from $0.05 to $0.14 per minute, before exclusions and required plan fees. That is only a starting point. Some rates cover the runtime alone, others include speech or model usage, and others add a…
- Bland AI vs Vapi: Which Stack Should You Run in Production?
Choosing between Bland AI and Vapi is an architecture decision. Compare how each platform handles providers, call flows, pricing, latency, concurrency, and production operations, with Dasha as a third option.
- Vapi vs OpenAI Realtime API: A Technical Decision Guide
Vapi and OpenAI Realtime can appear interchangeable when a team is budgeting a production voice agent, yet they sit at different layers. The decision changes who owns telephony, media transport, model choice, tools, testing, monitoring, and incident response. Technical teams need a current…
- Vapi vs Synthflow: Control, cost, and production fit
Vapi and Synthflow can both put a voice agent on the phone, but they use different operating models. Vapi gives developers a modular runtime with provider choice and usage-based hosting. Synthflow packages a visual build system, integrations, telephony options, and enterprise rollout support. The…
- AI for Client Account Management
AI in Client Account Management revolutionizes how businesses interact with clients, offering personalized experiences, automating routine tasks, and enhancing decision-making. This technology not only boosts efficiency but also strengthens client relationships, driving growth and satisfaction.
- AI for Airlines: Customer Service Pilots That Stay Grounded
The best first use of voice AI at an airline is a narrow customer-service pilot: answer from approved sources, retrieve live passenger data only through authorized systems, and transfer whenever the request is consequential or uncertain.
- AI for Asset Management Services
AI in Asset Management Services revolutionizes the industry by enhancing decision-making, optimizing portfolio performance, and reducing operational costs. This cutting-edge technology empowers firms to stay competitive and deliver superior value to clients.
- AI for Financial Auditing
AI in financial auditing revolutionizes accuracy and efficiency, uncovering insights that traditional methods might miss. By automating routine tasks, it allows auditors to focus on complex analysis, ensuring more reliable and timely financial assessments.
- AI for B2B Marketing: Workflows, Controls, and Metrics
AI can help B2B marketing teams research accounts, prepare content, qualify opted-in prospects, and keep campaign systems current. Useful deployments give models narrow tasks, verified data, limited tools, and a clear path to a person.
- AI for B2B Sales
AI is revolutionizing B2B sales by enhancing customer interactions, automating processes, and driving growth. Its ability to analyze data and predict trends empowers businesses to make smarter decisions, ultimately boosting efficiency and revenue.
- AI for Banking Services
AI is revolutionizing banking services by enhancing customer experiences, streamlining operations, and bolstering security. Its ability to analyze vast amounts of data in real-time offers unprecedented efficiency and personalization, making it an indispensable tool for modern financial institutions.
- AI for Behavioral Insights
AI in Behavioral Insights revolutionizes how businesses understand and predict customer behavior, offering unparalleled accuracy and efficiency. By leveraging advanced algorithms, companies can make data-driven decisions that enhance customer experiences and drive growth.
- AI for Budget Analysis
AI in Budget Analysis revolutionizes financial planning by providing accurate insights, automating tedious tasks, and enhancing decision-making. This technology empowers businesses to optimize resources and drive growth efficiently.
- AI for Business Operations Management
AI revolutionizes Business Operations Management by enhancing efficiency, reducing costs, and driving innovation. Its ability to analyze vast data sets and automate routine tasks empowers businesses to make smarter decisions and stay competitive in a rapidly evolving market.
- AI for Call Centers: Architecture, Handoffs, and QA
AI can handle a defined call-center transaction, assist an employee during a call, or structure completed-call data. The hard part is connecting the model to reliable systems, containing its authority, and transferring exceptions without losing context.
- AI for Oncology Research
AI is revolutionizing oncology research by accelerating discoveries, enhancing diagnostic accuracy, and personalizing treatment plans. This transformative technology promises to improve patient outcomes and streamline the research process, making it an indispensable tool in the fight against cancer.
- AI for Candidate Screening: A Human-Governed Design
AI can support candidate communication and collect job-relevant information, but it should not decide who advances. A defensible design keeps recruiters accountable, validates every criterion, accommodates candidates, and provides an audit and appeal path.
- AI for Car Sales: Practical Dealership Workflows
AI can help a dealership respond to inventory questions, schedule appointments, collect lead details, and prepare follow-up work. The useful version is connected to current dealership systems, limited to approved actions, and designed to hand pricing, financing, trade-ins, exceptions, and final…
- AI for Case Management: Human-Owned, Auditable Workflows
AI can help case teams collect information, summarize records, retrieve approved guidance, draft routine communications, and coordinate follow-up. It should support a named case owner, preserve source evidence, and leave eligibility, rights, discipline, benefits, money, safety, and other…
- Conversational AI Development: A Practical Chatbot Guide
Conversational AI development combines a language model with state, approved knowledge, business tools, safety controls, and testing. This guide shows what each layer should do and how to build a chatbot that can be evaluated before it reaches users.
- AI for Chat Support
AI in chat support revolutionizes customer service by providing instant, accurate responses, enhancing user experience, and reducing operational costs. This technology ensures businesses stay competitive while meeting customer expectations efficiently and effectively.
- AI for Coaching: Useful Workflows, Human Limits, and a Pilot Plan
AI can support practice, reflection, and coaching administration. It should not impersonate a qualified coach, diagnose a person, or make employment, health, or other consequential decisions.
- AI for Cold Calling: A Compliance-First Pilot Guide
AI can run bounded outbound conversations, but it does not make a call lawful or persuasive. Start with consent, suppression, disclosure, human handoff, and audit controls.
- AI for Construction Operations
AI is revolutionizing construction operations by enhancing efficiency, reducing costs, and improving safety. Its ability to analyze vast data sets and predict outcomes is transforming how projects are managed, making the industry smarter and more responsive.
- AI for Consulting
AI in consulting revolutionizes decision-making, offering data-driven insights and automating routine tasks. This empowers consultants to focus on strategic initiatives, enhancing efficiency and delivering unparalleled value to clients.
- AI for Contract Management Services
AI in Contract Management Services revolutionizes how businesses handle agreements, offering unparalleled efficiency, accuracy, and compliance. By automating tedious tasks, AI empowers companies to focus on strategic growth and mitigate risks, transforming contract management into a seamless,…
- AI for Corporate Communications
AI is revolutionizing corporate communications by enhancing efficiency, personalizing interactions, and automating routine tasks. This transformation not only boosts productivity but also fosters stronger connections with stakeholders, making it an indispensable tool for modern businesses.
- AI for Cost Assessment
AI in cost assessment revolutionizes financial planning by providing accurate, real-time insights. This technology enhances decision-making, reduces errors, and optimizes resource allocation, making it indispensable for businesses aiming to stay competitive and efficient.
- AI for Credit Analysis
AI in credit analysis revolutionizes financial decision-making by enhancing accuracy, reducing risk, and speeding up processes. This cutting-edge technology empowers institutions to make smarter, data-driven decisions, ultimately benefiting both lenders and borrowers.
- AI for Criminal Justice Operations
AI is revolutionizing criminal justice operations by enhancing efficiency, accuracy, and fairness. From predictive policing to streamlined case management, AI's capabilities are transforming how justice is served, ensuring a more effective and equitable system for all.
- AI for Decision-Making Support
AI in decision-making support revolutionizes how businesses operate, offering unparalleled accuracy, speed, and efficiency. By leveraging advanced algorithms, AI empowers organizations to make data-driven decisions, enhancing productivity and driving growth.
- AI for Defense Operations
AI is revolutionizing defense operations by enhancing decision-making, improving efficiency, and bolstering security. Its ability to process vast amounts of data swiftly and accurately makes it indispensable for modern military strategies.