How to Choose a Conversational AI Vendor for Telephony Infrastructure
Your team signed a six-month contract with a conversational AI vendor, built the agent, and launched it on 200 inbound lines. By week three, 14% of calls were dropping mid-sentence, transfers failed silently, and your SIP trunk provider blamed the AI platform while the AI platform blamed the SIP trunk. According to Gartner research, conversational AI will reduce contact center labor costs by $80 billion in 2026, but only for teams that get the telephony layer right.
This guide walks you through evaluating conversational AI vendors specifically on telephony infrastructure management, so you can avoid the integration failures that derail most first deployments. By the end, you will have a scored vendor shortlist and a testing plan that verifies call handling under real production conditions using Retell AI as the benchmark.
A structured vendor evaluation framework that tests conversational AI platforms against the telephony criteria that determine whether your agents survive real phone traffic.
By the end of this tutorial, your evaluation will:
Before you start, you'll need:
You cannot evaluate a vendor's telephony capabilities without knowing what you are connecting it to. Document your existing phone infrastructure in a single reference sheet.
Record your SIP trunk provider (Twilio, Telnyx, Vonage, or on-premises PBX), the number of concurrent call paths, your average and peak call volumes, and the codecs your system supports. Note whether you need to keep your current numbers, whether you use E911, and whether calls route through a contact center platform like Genesys or Five9. Include your compliance requirements: HIPAA, SOC 2, PCI-DSS, TCPA, or state-specific regulations. The FCC confirmed in 2024 that AI-generated voices fall under TCPA restrictions, so every vendor you evaluate must support consent management and AI disclosure at the call level.
You should now have a one-page telephony environment document that every vendor evaluation references.
Without a structured scorecard, vendor demos devolve into feature tours that obscure the criteria that matter in production.
Build a weighted evaluation matrix covering eight categories: SIP trunk compatibility (can the vendor connect to your existing trunk without replacing it), response latency (measured end-to-end, not just LLM inference), concurrent call stability (performance under your peak volume), call transfer reliability (warm handoff with context), number portability and provisioning, compliance certifications matching your industry, post-call data access (transcripts, analytics, structured metadata), and pricing transparency (per-minute breakdown with no hidden telephony surcharges). Weight each category based on your environment. A healthcare organization running inbound scheduling will weight HIPAA and call transfer higher. An outbound sales team will weight concurrent call capacity and batch call throughput higher.
You should now have a spreadsheet with eight weighted criteria ready to score each vendor.
Most vendor evaluation failures happen here. A platform that works in demos can fail when connected to your actual telephony infrastructure.
Request a test environment from each vendor. Connect your existing SIP trunk and run 50 test calls covering: inbound call pickup (measure time from ring to agent response), outbound call initiation, mid-call DTMF handling, and codec negotiation. Retell AI supports direct SIP trunking to any provider, so your existing Twilio, Vonage, Telnyx, or on-premises PBX connects without replacing your current stack. Vendors that require you to port numbers to their proprietary telephony or cannot accept a standard SIP INVITE are a red flag. Test with your actual trunk, not a sandbox number the vendor provides, because production SIP behavior differs from demo environments.
You should now have SIP compatibility results showing connection success rates and any configuration issues per vendor.
Callers hang up when pauses exceed two seconds. A vendor that responds in 800ms during a demo may hit 3 seconds under 50 concurrent calls.
Set up a load test simulating your peak concurrent volume. Measure end-to-end latency: the time from the caller finishing a sentence to the AI voice agent starting its response. Run tests at 25%, 50%, 75%, and 100% of your peak volume. The platform you are benchmarking against should maintain sub-second latency across load levels. Retell AI's architecture delivers approximately 600ms end-to-end latency with proprietary turn-taking that includes interruption recovery and barge-in handling. Record whether latency degrades linearly or collapses at a threshold. Platforms with shared infrastructure often degrade nonlinearly, meaning performance is acceptable at 30 concurrent calls and unusable at 50.
You should now have a latency curve per vendor showing performance across your volume range.
Failed transfers are the highest-risk telephony event. A caller who gets disconnected during an escalation will not call back.
Test three transfer scenarios per vendor: warm transfer to a human agent with full conversation context passed, cold transfer to an external number, and transfer to a department-based routing queue. Verify that the receiving agent sees a summary of what the caller discussed, not a blank screen. Test what happens when the transfer target does not answer within 30 seconds: does the caller get returned to the AI agent, dropped into voicemail, or disconnected? Also test book appointments workflows where the AI needs to hold the line while checking an external calendar API during the conversation. Retell AI's function calling executes real-time HTTP calls during the conversation, so calendar checks and CRM writes happen while the caller is still on the line.
You should now have transfer success rates and failure behavior documented for each vendor.
A vendor that checks a compliance box on a slide deck may not enforce it at the telephony layer where data exposure happens.
Verify certifications with documentation, not marketing claims. For healthcare deployments, confirm HIPAA compliance with a self-service BAA (not a "contact sales" gatekeeper). For financial services, confirm SOC 2 Type II audit reports are current. For outbound calling, verify TCPA-compliant consent management, AI identity disclosure mechanisms, STIR/SHAKEN support, and DNC list integration. Check data residency: where are call recordings stored, who has access, and what is the retention policy? Test PII redaction by running calls that include social security numbers, credit card numbers, or health information, and verify that transcripts redact the sensitive data. The platform should support configurable data retention and role-based access controls.
You should now have a compliance verification matrix showing which vendors meet your specific regulatory requirements with documented proof.
Vendor pricing pages show starting rates. Your actual cost depends on call duration, concurrency, telephony fees, and features that may be gated behind enterprise tiers.
Build a total cost model using your real call data: average calls per month, average call duration, peak concurrent calls, and feature requirements (transfers, knowledge base queries, analytics). Request an itemized cost breakdown from each vendor that separates AI processing, telephony, and platform fees. Watch for hidden costs: per-transfer surcharges, knowledge base query fees, analytics dashboard charges, or minimum commitment penalties. Retell AI charges $0.07/min starting with no platform fees, no per-feature surcharges, and $10 in free usage credits at signup. Compare this to vendors quoting enterprise contracts starting at $150,000/year that bundle features you do not need. The goal is cost per resolved call, not cost per minute, because a faster agent with higher containment costs less per outcome.
You should now have a 12-month cost projection per vendor based on your actual volume.
A two-week pilot on live traffic reveals problems that no demo or load test can simulate.
Deploy your top-scoring vendor (and a parallel backup if budget allows) on a subset of your live call traffic, between 10-20% of inbound volume. Configure post call analysis dashboards tracking: call completion rate, average latency, transfer success rate, containment rate, and caller sentiment. Review transcripts daily during the first week. Look for: calls where the AI misunderstood the caller, conversations that looped without resolution, transfers that lost context, and edge cases your test scenarios did not cover. Set a go/no-go threshold before the pilot starts (for example, 85% containment, sub-1-second latency, 95% transfer success). Plan for a 2-week tuning period: most teams see 70-80% containment in week one, improving to 85-95% after adjusting knowledge base content and escalation rules.
You should now have production performance data from live calls to make a final vendor selection.
Vendor-provided test numbers bypass the exact integration points that fail in production: codec negotiation, NAT traversal, and trunk registration timeouts. Connect your existing SIP infrastructure during evaluation so you see real behavior, not demo conditions. If a vendor cannot connect to your trunk in the trial phase, they will not connect reliably in production either.
A platform with advanced LLM capabilities and unstable telephony will lose more calls than a platform with solid call handling and adequate AI. When scoring vendors, give telephony criteria (latency, concurrency, transfer reliability) at least 40% of your total weight. Features like sentiment analysis and custom voices matter, but only after the call stays connected.
A $0.05/min vendor with $500/month platform fees, per-transfer charges, and analytics add-ons costs more than a $0.07/min vendor with no platform fees and included analytics. Build a 12-month TCO model with your real volume before comparing offers. Include the cost of engineering time for integration, because platforms requiring custom SIP configuration add weeks of setup that vendor-managed telephony eliminates.
If your call volume exceeds 10,000 calls per month, run two vendors in parallel on separate call segments during the pilot phase. This gives you direct comparison data under identical conditions and a fallback if one vendor's telephony layer fails. The incremental cost of a second pilot is small compared to the risk of a single-vendor production failure.
Teams often select a vendor based on how natural the AI sounds in a web demo, then discover the platform drops 8% of calls when connected to their SIP trunk. AI quality means nothing if the call does not stay connected. Always test telephony stability before evaluating conversation quality.
"SIP compatible" on a vendor's feature page can mean anything from native SIP trunk management to a third-party gateway that adds 200ms of latency. Ask specifically: does the platform manage SIP trunking natively, or does it rely on an intermediary? Intermediary gateways add failure points and latency that degrade caller experience.
A platform that handles 5 simultaneous test calls perfectly may degrade at 50. Most vendor evaluation processes test sequentially, one call at a time. If your production environment requires 20 or more concurrent calls, test at that volume before signing. Every Retell AI account includes 20 free concurrent calls, scalable higher for enterprise deployments.
Teams test whether transfers succeed but rarely test what happens when they fail. Does the caller get disconnected? Does the system retry? Does the AI agent resume the conversation? Transfer failure behavior under edge conditions (target busy, target unreachable, network timeout) separates production-grade platforms from demo-grade platforms.
Vendors that require you to port all numbers to their proprietary phone system create lock-in and add weeks of migration risk. Prioritize platforms that connect to your existing telephony via standard SIP trunking. Your phone system should not change because you added AI to answer calls.
Medical Data Systems deployed AI voice agents for inbound call handling in their collections operation. The result: 100% of inbound calls handled by AI with only a 30% transfer rate, collecting approximately $280,000 per month while scaling without additional telephony infrastructure.
SWTCH, an EV charging company, deployed an AI voice agent for customer support. Their agent answers calls in seconds, cut support costs by over 50%, and significantly improved SaaS margins by handling urgent EV driver support at scale across their existing phone system.
Matic Insurance automated call workflows for claims intake. They handled 8,000+ calls in Q1 2025, maintained an NPS of 90, and reduced claims handle time from 12.4 to 5.8 minutes, a 53% reduction, without replacing their existing telephony infrastructure.
You need either a SIP trunk from any provider (Twilio, Telnyx, Vonage, or on-premises) or the ability to assign new phone numbers through the vendor. Retell AI supports both: connect your existing trunk via AI IVR or provision numbers directly through the platform. No proprietary hardware is required.
Measure three metrics during a pilot: end-to-end response latency (under 1 second is the target), call completion rate (percentage of calls that end normally versus being dropped), and turn-taking quality (how the agent handles interruptions, crosstalk, and pauses). Test all three under concurrent load matching your peak volume.
Pricing models vary significantly. Per-minute platforms range from $0.07 to $0.15/min depending on features. Enterprise contract vendors start at $150,000/year or higher. Retell AI starts at $0.07/min with no platform fees, no minimums, and $10 free credit at signup. Always model total cost using your actual call volume, not the vendor's "starting at" rate.
For most teams, yes. Assembling separate STT, LLM, TTS, and telephony components requires engineering resources to maintain latency, handle failovers, and debug cross-vendor issues. A platform with integrated telephony management, like Retell AI, handles SIP trunking, voice synthesis, and call routing in a single stack, reducing integration complexity and total latency.
Verify the vendor supports: AI identity disclosure at the start of every call, consent tracking and revocation management, STIR/SHAKEN caller authentication, DNC list integration, and call recording with configurable retention. The FCC's 2024 ruling classifies AI-generated voices as "artificial" under the TCPA, so every AI telemarketing or outbound call requires prior express consent.
With SIP-based platforms, yes. Your existing numbers stay with your current trunk provider. The AI platform connects to your trunk and answers calls on those numbers without porting. Vendors that require number porting add migration risk and create lock-in. Ask this question early in evaluation: it reveals whether the vendor treats telephony as an open layer or a proprietary dependency.
Plan for 2-3 weeks of structured evaluation (scorecard, SIP testing, load testing, pilot) followed by a 2-week production tuning period. The no-code agent builder on Retell AI means you can start testing call flows within hours of signup, but thorough telephony validation and AI answering service tuning requires 4-5 weeks total before full production deployment.
Ask every vendor about their failover architecture: do they support automatic rerouting to a backup trunk, voicemail fallback, or forwarding to human agents during outages? Check their uptime SLA. Retell AI commits to 99.99% uptime with automatic failovers across LLM and TTS providers. Vendors without published uptime SLAs or documented failover behavior are a risk you should not accept for production call handling.
The telephony requirements differ by workflow. Lead qualification prioritizes outbound calling capacity, branded caller ID, and CRM integration. AI customer support prioritizes inbound call pickup speed, knowledge base accuracy, and transfer reliability. Evaluate vendors against the workflow that represents your highest call volume first, then expand.
You now have a structured framework for evaluating conversational AI vendors on the telephony criteria that determine production success: SIP compatibility, latency, concurrency, transfer reliability, compliance, and total cost.
To start your evaluation, sign up for Retell AI and connect your existing SIP trunk to benchmark call quality, latency, and transfer behavior against other vendors on your shortlist. From there, extend the same agent to handle call center automation workflows or deploy conversational AI across additional phone lines.
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