Bland achieves FedRAMP 20x Class A Certification for voice AI platform. Sep 01, 2026, 09:00 ET Bland becomes the only voice AI platform to achieve FedRAMP 20x Class A Certification, giving federal agencies a new path to evaluate and adopt AI agents SAN FRANCISCO, Sept. 1, 2026 /PRNewswire/ - Bland, the enterprise voice AI platform, today announced that it has achieved FedRAMP 20x Class A Certification for its voice, SMS and chat agents. Bland is now listed on the FedRAMP Marketplace, giving federal agencies access to the security and certification information needed to evaluate the platform and pursue their own Authority to Operate. FedRAMP 20x is the federal government's new approach to cloud security certification, designed to make the process faster and more efficient through automation, machine-readable evidence and continuous monitoring. Rather than relying primarily on periodic assessments and static documentation, FedRAMP 20x requires providers to maintain certification data over time and provide ongoing visibility into security controls, vulnerabilities and incidents. Bland is not only the first voice AI platform to achieve FedRAMP 20x Class A certification, but the first company in America to do so. FedRAMP describes Class A Certifications as providing adequate information for most non-sensitive use cases and some Low, Moderate or High security objectives. Certification enables agencies to evaluate Bland and pursue authorization based on their individual requirements and use cases. "We built Bland to handle the highest-stakes phone calls in the world. The ones where getting it wrong isn't just a bad experience, it's a missed medical appointment or a benefits check that never arrives," said Isaiah Granet, co-founder and CEO of Bland. "FedRAMP 20x gives agencies a clear path to evaluate voice AI for these interactions. We built a dedicated government environment from the ground up so agencies can use AI while maintaining the security, reliability and control these conversations require." Bringing AI Agents to Government Services Bland enables organizations to automate conversations across voice, SMS and chat. Federal agencies can use the platform to handle inbound questions about benefits, applications and accounts, as well as outbound appointment reminders, deadline notifications and check-ins. The platform can also support structured data collection and verification workflows, such as earnings verification, background checks and program eligibility. SMS agents can extend these interactions beyond phone calls by sending reminders, collecting information and allowing people to continue conversations over text. Bland's architecture is designed for high-stakes conversations where reliability, security and predictable performance are critical. Bland is the only voice AI platform that owns its voice AI infrastructure rather than relying on third-party providers for critical components of the voice stack, giving Bland direct control over data handling, latency, reliability and system performance. Bland is American owned and operated. Bland completed the Class A certification process in record time, just 18 days from submission to approval. The company is now preparing its application for FedRAMP20x Class C Certification and has engaged an independent Third Party Assessment Organization for that process. Proven at Scale in High-Stakes Conversations Bland already operates at significant scale across commercial environments. One of the largest survey research firms uses Bland to place 25,000 outbound calls per hour with half-second latency and 99.9% uptime. A consumer lending servicer uses Bland to authenticate callers and collect compliant payments across 3,000 calls per day. A Fortune 1000 insurer reduced its cost per call from $45 to $0.29 by replacing outsourced and manual outreach with Bland. The same infrastructure gives federal agencies a way to automate high-volume, high-stakes conversations while maintaining control over how agents behave, what actions they can take and how data is handled. Bland's FedRAMP 20x certification is listed on the FedRAMP Marketplace under ID FR2628647242. About Bland Bland is the voice AI platform trusted with the world's highest-stakes phone calls. It's the only voice AI platform that's entirely self-hosted, providing the security, reliability, and predictability the hardest calls demand. Built for regulated industries, Bland handles inbound and outbound calls end-to-end, so companies can cut support headcount without risking a costly mistake. Visit https://bland.com/ to learn more. SOURCE Bland

AI voice agent platform: how to choose the right one in 2026. Persistence Team · August 26, 2026 On this page Key takeaways * There is no single best AI voice agent platform. Independent tests from Ventureharbour and Arahi both put Vapi, Retell AI, and Bland AI in their top tier for latency and reliability (ventureharbour.com, arahi.ai). * Retell AI shows up first in nearly every 2026 ranking, including Vellum's guide and its own blog, but vendor-published lists should be read as one data point, not the final word (vellum.ai, retellai.com). * Cost is usually billed per minute of call time, and per-minute cost is exactly what Ventureharbour's hands-on test set out to measure across 7 platforms (ventureharbour.com). * For raw voice quality, ElevenLabs' models are the ones most platforms license or benchmark against, since ElevenLabs sells voice agents built on its own speech models (elevenlabs.io). * Developer-first platforms like Vapi let you plug in different LLMs and voice models rather than locking you to one stack (vapi.ai). What an AI voice agent platform actually does. An AI voice agent platform is the infrastructure layer that turns a phone call into a conversation with software. It handles speech-to-text, a language model that decides what to say, text-to-speech, and the telephony that connects it all to a real phone number. Vapi describes itself this way directly: a platform for developers building and deploying voice AI agents (vapi.ai). Bland AI positions itself similarly for enterprises, emphasizing self-hosted models and sub-second latency (bland.ai). No-code options like OmniDimension aim at businesses that want a voice agent without writing code, covering calls, lead capture, and 24/7 coverage (omnidim.io). The honest answer is that it depends on what you're testing for, and the rankings shift depending on who wrote them. Ventureharbour built voice agents on 7 tools - including Vapi, Retell, Synthflow, and Bland - and tested them hands-on for latency and cost-per-minute rather than relying on marketing claims (ventureharbour.com). Arahi ran a similar test across 11 platforms, ranking Vapi, Retell, Bland, Synthflow, and ElevenLabs on latency, voice quality, and telephony (arahi.ai). Vellum's 2026 guide ranks Retell AI first, followed by SquadStack, Leaping AI, PolyAI, Bland AI, Voiceflow, and Sierra AI (vellum.ai). Retell AI's own blog also puts itself first, ahead of PolyAI, Cognigy, CloudTalk, Lindy AI, and Synthflow - useful for seeing how it stacks itself against competitors, but worth reading with that context in mind (retellai.com). The pattern across independent tests: Vapi, Retell AI, and Bland AI consistently place near the top. The top 3 AI voice agent platforms, by how often they rank well. Across both vendor lists and independent hands-on tests, three names repeat: Retell AI, Vapi, and Bland AI. Retell AI appears first in Vellum's independent guide and in its own comparison (vellum.ai, retellai.com). Vapi is built specifically for developers who want to build voice agents in minutes and shows up in both the Ventureharbour and Arahi hands-on tests (vapi.ai, ventureharbour.com, arahi.ai). Bland AI markets itself on enterprise compliance, self-hosted models, and sub-second latency, and also appears across all three independent comparisons (bland.ai, ventureharbour.com, arahi.ai, vellum.ai). PolyAI and Synthflow are the next most frequently cited names, particularly for customer support use cases (retellai.com, vellum.ai, arahi.ai). Most platforms bill by the minute of call time rather than a flat monthly fee, which is why Ventureharbour's comparison specifically measured cost-per-minute across the 7 platforms it tested rather than just listing subscription tiers (ventureharbour.com). That per-minute model matters more than a headline price, because your actual bill scales with call volume and average call length. If you're comparing platforms, ask for cost-per-minute at your expected call volume and length, not just the plan price, since that's the number independent testers actually rely on to compare tools apples-to-apples. This splits into two separate questions: which model generates the voice, and which model decides what to say. ElevenLabs is the name most associated with voice quality - it sells voice agents built directly on its own speech models and markets them for real-time, human-like conversations (elevenlabs.io). For the reasoning layer, developer-first platforms like Vapi are built so you can plug in different LLMs rather than being locked to one (vapi.ai). Community discussion on Reddit's r/AI_Agents reflects the same split: builders mix and match a speech model, an LLM, and a telephony layer rather than picking one all-in-one model for everything (reddit.com). A simple way to evaluate any platform. Test the same three things every independent review tested: latency (how long before the agent responds), voice quality (does it sound natural on a real phone line, not just a demo), and cost-per-minute at your expected volume. Ventureharbour and Arahi both built real agents and measured these directly instead of trusting spec sheets (ventureharbour.com, arahi.ai). Whatever platform you land on, run your own test call before committing - rankings change fast in this category, and both Ventureharbour and Arahi's guides are dated 2026, meaning even recent lists get outdated within months. For related guidance, continue with Upfirst AI Receptionist: Pricing, Features, and Whether It's Worth It and Nextiva AI Receptionist: What XBert Does and What It Costs. Related resources. Frequently asked questions. Which AI voice agent platform is best? How much do AI voice agents cost? Which AI model is best for voice agents? Try persistence. Persistence Automate your calls. Connect with Persistence.

Bland AI vs Vapi: building high-performance outbound AI voice agents. Comparing outbound sales scripting, telephony API pathways, webhook latency, and pricing configurations Ethan Walker August 6, 2026 ~3,000 words Telephony is undergoing a massive transformation. In 2026, companies are moving away from traditional call center IVR menus and human-based cold calling, shifting toward fully autonomous AI voice agents. These voice assistants are no longer simple static scripts; they converse, handle pricing objections, schedule calendar invitations via webhooks, and record comprehensive call logs at a fraction of the cost of a human agent. To make voice interactions feel natural, latency is the ultimate metric. A response latency of over 1.5 seconds immediately signals to a customer that they are talking to a bot, driving down pick-up conversion rates. Sub-second response times are the baseline requirement for professional outbound calls. Bland AI and Vapi are the two dominant platforms leading this space, but they solve this problem using entirely different architectural approaches. In this technical comparison guide, Needaitool evaluate Bland AI and Vapi on voice agent latency, visual scripting tools, custom LLM integrations, telephony SIP vendor options, and pricing structures for outbound campaigns. The core telephony pipeline: where latency lives. When building an AI voice agent, every spoken sentence must progress through four sequential steps: Speech-to-Text (STT) transcription, Large Language Model (LLM) logical processing, Text-to-Speech (TTS) voice synthesis, and SIP/VoIP audio streaming. The sum of these operations determines the overall call response latency. Bland AI achieves a sub-second response time (~800ms) by utilizing an integrated pipeline. They host their own custom voice-retuned LLM instances and cache active TTS voices directly on the telephony servers. This eliminates the roundtrip latency of calling external APIs. Vapi takes a modular approach, acting as a high-performance orchestration layer. It lets you select modular providers for each block: Deepgram for STT, OpenAI or Anthropic for LLM, and ElevenLabs or Cartesia for TTS. While this gives developers maximum flexibility, Vapi's modular API roundtrips result in a slightly higher latency of ~1.1s. While Vapi has optimized its web sockets to get close to sub-second speeds, Bland's unified hardware stack maintains a slight latency edge in outbound call environments. Visual scripting pathways vs. Telephony APIs. For outbound sales campaigns, call logic is rarely a straight line. Conversations branch depending on prospect objections: 'I don't have time right now,' 'Is this a sales call?', or 'How much does it cost?'. Building these branching paths in raw code or basic prompts quickly becomes messy. Bland AI solves this with 'Pathways', a visual flow builder. It lets non-technical managers map out call routes using nodes. You can define specific greeting hooks, branch to an objection handler node, trigger an external calendar invite webhook, and route to a call wrap-up node based on user replies. It acts like a visual blueprint for conversational AI. Vapi takes an API-first approach, letting developers code conversational flows. Instead of a visual builder, Vapi relies on prompt instructions, custom functions, and server-side webhooks. This is ideal if you have a software development team building complex inbound call centers that need to fetch user data from a company CRM, make real-time account queries, and route caller actions dynamically using standard JSON code payloads. Bland AI deep dive: the outbound sales powerhouse. Bland AI was built specifically for outbound calling campaigns. It features a high-concurrency dialer capable of triggering 10,000+ outbound calls simultaneously. It handles standard telephony challenges like voicemail detection (answering machine detection), call routing, and SIP trunk concurrency limits natively. Additionally, Bland AI hosts their own custom LLMs that are fine-tuned on thousands of sales call transcriptions. This makes their voice agents highly skilled at handling objections, steering conversations back to the sales script, and identifying the perfect closing window to book a meeting or trigger a payment invoice link. Bland AI core features. * Pathways: Visual conversational logic builder with custom node paths * High-concurrency dialer for bulk outbound campaigns * Fine-tuned sales LLMs with native voicemail detection (AMD) * Post-call summary webhooks: automatically exports transcriptions, sentiment analysis, and parsed form data Pricing: $0.12 per call minute (all-inclusive for voice, LLM, and telephony). Best for: Lead generation agencies, outbound sales teams, and collection agencies seeking high concurrency. Vapi deep dive: the modular developer platform. Vapi is the developer's dream. It doesn't restrict you to a single vendor stack; instead, it acts as a flexible orchestration layer. You can integrate your own custom LLM API endpoints, purchase phone numbers from Twilio or SignalWire, connect custom SIP trunks, and select from a diverse list of neural voice providers (ElevenLabs, Play.ht, Cartesia, Neets, etc.). This modularity is particularly useful for inbound customer support helpdesks. Vapi lets you stream customer conversations back to your private servers, execute backend database queries mid-call, and return localized customer balance or order details dynamically. Vapi also supports smart interruption handling, letting customers interrupt the agent naturally during speech. Vapi core features. * Modular architecture: Connect your own Twilio numbers, SIP trunks, custom LLMs, and TTS keys * Smart interruption handling with voice activity detection (VAD) * Real-time client streaming SDKs for web and mobile apps * Function calling: Trigger mid-call CRM database queries and webhook parameter checks Pricing: Vapi charges an orchestration fee of $0.05/minute, plus external provider fees (average combined minute cost: $0.09 - $0.15/minute). Best for: Inbound customer support centers, SaaS software developers, and enterprise teams needing full pipeline customization. Side-by-Side technical comparison. | Technical Feature | Bland AI Platform | Vapi System Orchestrator | | Average Call Latency | 750ms - 900ms (Excellent) | 1.0s - 1.2s (Good) | | Conversation Scripting | Visual Pathways Drag-and-Drop Editor | Developer Prompts & Function API | | Telephony Integration | Integrated SIP & Dialers | Modular Twilio, SIP, web/app SDKs | | Voicemail Detection (AMD) | Custom fine-tuned system (AMD) | Twilio AMD / Vapi VAD detection | | Active Minute Cost | $0.12/minute flat | $0.05/min orchestration + provider costs | Which voice platform should you Choose? The ideal tool depends entirely on your campaign direction and team skillset. Here is its decision map: * Choose Bland AI if your focus is outbound sales, lead generation, or bulk call dialers. The Pathways visual flow builder makes script adjustments straightforward, and the integrated pipeline guarantees low conversational response times. * Choose Vapi if you are building inbound customer service centers, developing web/mobile app conversational interfaces, or need full custom developer controls over SIP trunks, LLM logic routing, and TTS providers. Conclusion. Voice AI agents have progressed from robotic text-to-speech tools into highly dynamic conversational representatives. In outbound sales, Bland AI is the current gold standard due to its visual Pathways designer, high concurrency limits, and sub-second integrated server latency. Vapi, on the other hand, remains the leading modular developer platform, allowing software teams to connect custom VoIP systems and private database services. Deploying conversational AI voice agents cuts human call center costs by over 85%, increases outbounds dialing scale, and eliminates training pipelines completely, helping you convert prospects and support users in real time. Frequently asked questions. What is voice activity detection (VAD)? VAD is the technology that detects when a caller is speaking. In voice agents, VAD allows the bot to pause and listen when interrupted by a customer, making the conversation feel natural rather than talk-over-talk. Can AI voice agents dial cell numbers? Yes. Both Bland AI and Vapi route call outputs through standard telephony SIP trunks (like Twilio, SignalWire), allowing them to dial any standard mobile or landline numbers worldwide. Is voice cloning safe for sales calls? Yes, when compliant with telephony regulations (FCC rules, TCPA acts, and regional outbound guidelines). It is recommended to clone the voices of consent-given company representatives to preserve brand trust, and clearly announce that the caller is an AI voice assistant when local statutes require it. Found this useful? Share it: Ethan Walker I'm a technology writer passionate about AI tools, automation, productivity software, and emerging SaaS platforms. I spend my time testing digital tools and breaking down complex technologies into practical insights that help businesses, creators, and professionals work smarter. AI tools mentioned in this Post. Marketing AI Automation AI SymphonyOS provides autopilot marketing for artists and creators. It automates marketing tasks so creators can focus on their work. freemium Verified