How to Choose an AI Voice Agent: Buyer's Guide

Two companies buy an AI voice agent for similar use cases in a similar timeframe. Company A opted for the cheapest option on the market, deployed it, and abandoned it two months later because it was useless for anything beyond simple calendar rescheduling. Company B spent an additional two weeks documenting its existing processes, selected the best-fitting platform, and deployed within a month, handling real traffic with ease.

Same category of product, different results. In almost all cases, it has little to do with the platform's language model being objectively better than the other platform’s. It has to do with the buyer's understanding of the task before choosing the platform.

This article will walk through the process of figuring out what you actually need from an AI voice agent. It covers the questions to ask to define clear business goals, what to test and enquire about on a candidate platform to ensure it supports your workflows, and what to ask to differentiate between a proof-of-concept and production-grade deployment.

Start with Your Business Goals

Most buying guides start the discussion with features and capabilities. But these are often amongst the last things you should consider when choosing an AI voice agent. Real-world buying processes from companies that have deployed such products always begin with a simple question: what problem do you intend to solve by deploying an AI voice agent?

"We want an AI voice agent" is not a definition of success. "We want to qualify inbound solar leads before routing them to a sales agent" qualifies as a business goal. It is broad but specific enough to begin comparing potential solutions.

A rough equivalence table of business goals and their implications is below.

None of these are the "right" or "wrong" goals. They are just examples of goals. A real-world example of a company that began with a goal of improving customer support was Homeday, a real-estate brokerage in Germany. They identified that their in-house capacity could not keep up with the demand for customer support, specifically regarding property viewings and valuation enquiries. They deployed telli as an AI voice agent to field these calls at any time of the day and night, responding to most inbound calls directly or routing them to the appropriate human representative without increasing their staff headcount.

A solar and heating franchise network, enerix, had an issue with their lead generation and qualification process being scattered across their network of franchises. They selected an AI voice agent to field their inbound calls to screen leads and capture necessary information before passing them to the franchise in their territory. As a result, they saw their completed call volume increase by a factor of four within sixty days of deployment, qualifying more leads for their sales team.

The point is that the company is expected to understand its own needs before evaluating solutions. In both cases, the companies were able to rapidly identify the appropriate voice agent solution because they knew what they were looking for.

Identify Your Required Workflows

With the business goal or goals established, you should move on to detail what has to happen at every stage. This is the most important step in selecting an AI voice agent, the one that most companies overlook. You must describe the end-to-end interaction with the customer in enough detail for an outsider to understand what you expect from the technology. You should be able to write a short paragraph about each step in the process.

A simple version of that chain looks like:

Every step in this chain represents a potential point of failure for a prospective voice agent platform. A platform that cannot push updates to your CRM or check your calendar cannot be a good fit for such a use case, regardless of how impressive you find its demo.

This is equally applicable to other domains, such as recruitment calls. Zenjob, a staffing platform, wanted to improve its candidate screening process. The goal was to allow an AI to conduct an initial information-gathering call with candidates before passing them to a human recruiter for further screening. They automated the first call using an AI voice agent, which now handles 90% of these information-gathering calls and cuts the time recruiters spend on initial candidate calls by 75%.

When in doubt, ask to see a proof-of-concept for your workflow and not just a generic demo.

Evaluate Core AI Capabilities

Feature lists are useful as a starting point, but not much beyond that. You should know what capabilities a voice agent platform has, but you should always ask to understand what happens when things go wrong. Examples of capabilities to enquire about include the following.

• Speech recognition accuracy: affects first-call resolution rates directly. Ask about variation in performance based on accents, background noise, and line quality.
• Latency: high latency hurts conversation flow. Ask for median and 95th-percentile response latency in production, not a demo.
• Knowledge base: defines how much domain-specific information the agent can retain. Ask to test how it handles a query it can't answer.
• Prompt control: determines how much you can adjust behaviour without engineering support. Ask if a non-technical team member can edit prompts unassisted.
• Human handoff: defines the transition policy in complex conversations. Ask if a human agent picking up the call gets the full context from the AI agent.
• Multilingual support: enables serving audiences in more than one language. Ask what happens if a caller speaks a language the agent isn't set up for.
• Conversation memory: determines whether the agent tracks context across a multi-step call. Ask if it remembers something said five minutes ago, or only the last turn.
• Analytics: the ability to operationalise insights from thousands of conversations. Ask to retrieve structured outcome data, not just raw transcripts.

You cannot always judge from a public demo. In particular, a one-call demo may be much more polished than the reality of thousands of customer conversations at once. Ask to see production performance from an existing customer if such an option is available.

Review Integration Capabilities

A voice agent that cannot be integrated with your existing infrastructure is little more than a fancy phone tree. Before selecting a new voice agent platform, you must define what connections it needs to support.

These include the following.

Must-have

• CRM sync (HubSpot, Salesforce, or your system of record)
• Calendar sync (e.g. Google Calendar or Outlook via Calendly or Cal.com)
• Telephony: a new number, call forwarding, or your own SIP trunk

Nice-to-have

• Slack or email notifications for handoffs
• Ticketing system integration for support use cases
• Webhook support for custom workflows

Enterprise-only

• Custom API development for proprietary internal systems
• SSO and role-based access control
• Dedicated data residency options

Some platforms will offer fewer, more specialised features in a given category, so it is important to understand your own requirements first. It is common for companies to overlook this stage of the evaluation process. Vendors may offer only a generic statement such as "we support integrations with X", but it is helpful to understand if your desired workflow is already production-proven or will require custom development.

Understand Pricing Models

AI voice agent pricing typically falls into several broad categories, which have different implications for cost savings and flexibility.

One nuance in per-minute pricing is that some vendors count hold time, silence, or transfer time as billed minutes, while others do not. It is critical to clarify exactly what is captured in billed minutes to evaluate plans against each other accurately.

Evaluate Security & Compliance

This section is often overlooked until it is too late. Note that any mention of personally identifiable information (PII), protected health information (PHI), and payment data requires the vendor to comply with data security standards, which vary depending on the industry. As a buyer, at the very least, you should ask the vendor which standards their infrastructure adheres to.

A quick reference on what each of the common frameworks actually covers:

• SOC 2: Trust service principles defined by an auditing standards organisation, AICPA. The standard covers five areas: security, availability, processing integrity, confidentiality, and privacy, of which security is mandatory, and the rest are optional depending on what the vendor commits to. In practice, this means asking the vendor which trust service principles they cover rather than asking whether the vendor is SOC 2 compliant, as a SOC 2 report is a document produced for external auditing purposes that will include specifics pertinent to that engagement.
• GDPR: The EU regulation that concerns processing and storage of personal data of EU residents, regardless of where the organisation is based. In practice, this means that if any EU residents are using the product and/or providing data to the vendor, the vendor needs to be GDPR compliant.
• HIPAA: United States standard for protecting electronic protected health information (ePHI) and a set of administrative, physical, and technical safeguards for handling PHI, enforced by HHS. This standard is particularly relevant to healthcare organisations, including their vendors and business associates, which are required to sign HIPAA business associate agreements with covered entities.

The following security measures are considered standard for most vendors covering basic confidentiality and integrity of customer data:

• Data encryption at rest and in transit: Vendors typically store and process data on their infrastructure, so encryption is a fundamental requirement.
• Audit logging: Logs should be available for every action taken by the call centre staff or an administrator, particularly calls and prompt updates.
• Access controls: Editors or administrators must have roles that grant access to features according to the least privilege principle.
• Retention/deletion policy: Data on both sides (customer and vendor) must be retained for a specific period defined by the agreement. This includes data erasure in case of termination of the agreement.
• Incident response policy: The vendor must have procedures for responding to security events reported by clients or identified internally.

Measure Platform Reliability

It is not always obvious until you are faced with a deluge of calls that the selected provider’s platform is unable to handle increased loads. It is essential to evaluate the vendor’s ability to process more calls in a higher workload environment.

Ask the vendor to share their SLA documentation (some may not have it) or review the service uptime and response times directly. SLA documentation will specify the conditions under which the vendor compensates the client for downtime and performance issues, so a vendor that cannot produce this documentation may be hiding their lack of reliability.

McMakler, a leading real estate brokerage with a 20-person customer care team, experienced call volume surges where queues at peak times sometimes reached 700–800% of active callers. The company made peak-hour call response times three times faster and decreased scaling costs by 90% without increasing headcount. After exploring two other AI call automation platforms, McMakler chose telli for its voice interaction, which it found far superior to the alternatives, and for scaling without growing its customer care team disproportionately.

Common Mistakes Buyers Make

• Comparing platforms on cost alone: the cheapest option may lack the integrations or reliability you need. Weigh overall cost to the business, not just the sticker price.
• Skipping a real workflow test: a promising vendor may turn out unable to handle the actual task. Request a test using your own workflow, CRM, or calendar before signing.
• Overlooking latency: a laggy conversation can be a dealbreaker for callers. Ask for production latency figures, or test it yourself.
• Treating security as a checkbox: violations of data security or retention policy can happen at any time. Ask for documentation rather than assuming compliance.
• Not involving frontline teams: a strong-looking agent may still have poorly crafted prompts. Get support or sales staff involved in prompt evaluation.
• Skipping analytics evaluation: thousands of unstructured transcripts are hard to draw insight from. Ask whether structured outcome reporting is available.

Downloadable AI Voice Agent Evaluation Checklist

Business fit

• Defined target business outcome: support, sales, scheduling, screening
• Mapped complete conversation lifecycle with the target agent, including the initial call
• Prioritised must-have and nice-to-have integrations

AI capabilities

• Tested speech recognition against your target demographics
• Tested latency in production or observed at least 5 minutes of conversation
• Observed how the agent handles a query the knowledge base does not cover
• Tested prompt editing process (no coding required)
• Observed if human handoff retains conversation history
• Tested multilingual support (if applicable)

Integrations

• Tested CRM integration
• Tested calendar integration
• Confirmed telephony setup (new number, forwarding, or SIP trunk)
• Confirmed availability of webhooks or APIs (if required)

Security & compliance

• Review SOC 2 report (trust service principles) or similar documentation
• Assessed if the vendor is subject to GDPR (any EU residents using the service)
• Confirmed HIPAA business associate agreement (if applicable)
• Reviewed data retention/deletion policies
• Confirmed audit logging and data access controls

Operations & reliability

• Reviewed SLA documentation
• Benchmarked or tested platform’s ability to handle higher call volumes
• Confirmed fallback process for telephony or integration failure

Pricing

• Assessed whether the plan type (per-minute, seat-based) matches call volume patterns
• Understood what is included in billed time (silence, hold, transfers)
• Identified additional costs (custom integrations, overage fees)

Support

• Clarified onboarding process and timeline
• Tested support responsiveness from current customers

Where This Leaves You

You can see from the evaluation framework that a business fit assessment precedes any discussion of the particular technologies involved. Once a company has identified one or several vendors capable of meeting the business requirements, the comparison becomes much more straightforward.

Sources Used

1. telli.com - Homeday Case Study: 24/7 Inbound Call Coverage
2. telli.com - enerix Case Study: Lead Capture for Franchisees
3. telli.com - Zenjob Case Study: Candidate Call Automation
4. telli.com - First Contact Resolution Rate Metric Guide
5. docs.telli.com - telli Call Transfers Documentation
6. secureframe.com - SOC 2 Trust Services Criteria Guide
7. commission.europa.eu - European Commission: Legal Framework of EU Data Protection
8. hhs.gov - U.S. Department of Health and Human Services: Summary of the HIPAA Privacy Rule
9. telli.com - McMakler Case Study: Managing Peak Call Wait Times