Rohan Pavuluri builds SIMBA Voice Agents at Speechify. Previously, he founded and led Upsolve, the largest nonprofit in the United States serving low-income Americans through technology. He writes about real-world voice-agent deployments — customer support, outbound sales, AI receptionists — and the practical product, design, and operational lessons that actually move the needle.
Articles by Rohan Pavuluri (95)
SIMBA vs Avoca: Which AI Voice Agent Platform Is Right for Your Service Business?
Avoca raised $125M at a $1B valuation for home services voice AI. SIMBA takes a different approach — horizontal platform, published pricing, IVR navigation, and a dedicated engineer for every customer.
Voice AI for Commercial Real Estate: Leasing, Tenant Services, and Property Operations
Commercial real estate has distinct communication patterns from residential. Voice AI handles leasing inquiries, building ops, CAM questions, and broker qualification across office, retail, and industrial.
Voice Agents for Tenant Communication: Maintenance, Rent, and Lease Management at Scale
Managing tenant communication at scale breaks at about 200 units per property manager. Voice agents handle the entire lifecycle — inquiries, applications, maintenance, rent, renewals, and move-outs.
Voice AI for Mortgage and Lending: Pre-Qualify Borrowers and Book Loan Officers Automatically
Loan officers spend 60% of their time on unqualified leads. Voice AI pre-qualifies borrowers, collects documents, and books consultations — so LOs focus on closeable deals.
AI Receptionists for Real Estate Offices: Never Miss a Showing Request Again
Real estate offices miss 40-60% of calls when agents are showing properties. AI receptionists answer instantly, check MLS availability, book showings, and route hot leads.
AI Voice Agents for Real Estate Lead Qualification: Convert More Zillow and Realtor.com Leads
Internet leads have a 5-minute response window. AI voice agents respond in under 60 seconds, qualify buyers on budget, pre-approval, and timeline, then warm-transfer hot leads to human agents.
Voice AI for Property Management: Automate Tenant Calls, Maintenance Requests, and Lease Renewals
Property managers spend $180/unit/year on phone support. Voice AI cuts that by 60-70% while improving tenant satisfaction with instant 24/7 response to maintenance, rent, and lease inquiries.
Voice AI for Property & Casualty Insurance: From First Quote to Final Settlement
P&C carriers spend $40-90M annually on call center operations. Voice AI automates the routine 70% across quoting, servicing, claims, and renewals — with Guidewire and Duck Creek integration.
Voice Agents for Insurance Policy Renewals: Reduce Lapse Rates and Retain More Policyholders
A 3-5% reduction in lapse rates can save a mid-size carrier $300K-$500K in annual premium. Outbound voice agents run renewal campaigns at scale for a fraction of agent costs.
AI Receptionists for Insurance Agencies: Answer Every Call, Qualify Every Lead
Insurance agencies miss 30-40% of calls during business hours. AI receptionists answer every call, qualify by line of business, and book producer appointments for $8-15K/year vs $40-54K for a human.
Voice AI for Commercial Insurance Brokerages: Automating Quotes, Submissions, and Client Service
Commercial brokerages drown in COI requests, E&S submissions, and renewal management. Voice AI handles the routine 70% so producers focus on relationships and complex placements.
AI Voice Agents for Insurance Enrollment: Medicare, AEP, and Open Enrollment at Scale
AEP call volumes spike 10x in 8 weeks. AI voice agents scale instantly with CMS-compliant scripts, SOA tracking, and deterministic disclosure handling — without seasonal hiring.
Voice AI for Insurance Claims Intake: How to Automate FNOL Without Losing Policyholder Trust
Claims intake is the highest-stakes call an insurance company takes. Voice AI handles structured FNOL collection conversationally, cutting cycle times by 40% and saving $850K+ annually at scale.
Why AI Voice Agents Will Replace Every IVR System
67% of customers have hung up on an IVR out of frustration. AI voice agents don't route callers through menus — they resolve the issue directly. The $22B voice AI market is replacing IVR across healthcare, financial services, property management, and legal.
Why the Last Mile of AI Deployment Is All That Matters
Every vendor can demo a voice agent that sounds amazing. Very few can make one that actually resolves your customers' calls at scale. The difference is the last mile of deployment — and most companies are on their own for it.
Forward Deployed Engineers: Why SIMBA Embeds with Your Team Instead of Handing You a Dashboard
Voice AI platforms love the word 'self-serve.' SIMBA took the opposite approach: every customer gets a dedicated engineer who joins their team. Here's why we believe customer obsession — not dashboards — is what makes AI actually work.
How Any Team Can Launch Its Own AI SDR for Outbound Calling
Hiring SDRs is slow, expensive, and unpredictable. Training takes months. Turnover averages 18 months. AI voice agents change the equation. With SIMBA, any team can launch a dedicated outbound calling agent in days, not quarters.
Why AI Voice Agents Are Replacing IVR — and How to Make the Switch
IVR was the right answer for the 1990s. Route calls with touchtone menus, play pre-recorded prompts, transfer to a human when the caller gives up and presses 0. There is now a better option — AI voice agents that resolve calls, not just route them.
ElevenLabs for Voice Agents: What You're Actually Paying For
ElevenLabs is excellent at text-to-speech. But if you're building conversational voice agents, you may be paying significantly more than you need to. Here's an honest breakdown of how the pricing model works and when it creates problems at scale.
SIMBA vs ElevenLabs Concurrency: Why It Matters for Production Voice Agents
SIMBA Pro includes 50 concurrent agents. Scale includes 500. Enterprise is unlimited. ElevenLabs caps at roughly 10 on comparable tiers. Here's why that matters when your phone lines are ringing.
SIMBA vs ElevenLabs Pricing: A Complete Comparison
SIMBA starts at $0.06/min with LLM included. ElevenLabs starts at $0.10/min with LLM costs that may be passed through. Here's what that means for your bill at 1K, 10K, 50K, and 500K minutes per month.
What Decagon, Sierra, and Fin Get Right About AI Support
Three AI support companies — Decagon, Sierra, and Fin (by Intercom) — have emerged as the most credible enterprise players in the AI customer service space in 2026.
What to Look for in a Voice Agent Vendor
Picking a voice agent vendor is like picking a cardiologist — you're putting something critical in their hands and you mostly can't verify their work until it's too late.
Voice Agent Pricing Models Compared
Voice agent pricing in 2026 is still a confusing mess. Vendors charge per-minute, per-call, per-month, per-seat, per-agent, and hybrid combinations of all of these. List prices don't match what enterprises actually pay. Some vendors bundle telephony, some don't.
Choosing a Voice Agent Platform in 2026: A Buyer's Guide
The voice agent market has crossed a threshold where the question has shifted from "can this technology work?" to "which platform should we buy?" The former is answered — sub-500ms latency, production-grade TTS, reliable function calling are all table stakes in 2026.
Network Outage Communications via Voice Agents
When a network outage hits, the phones light up. Cable outage takes down 50,000 households, and within minutes, the contact center is overwhelmed. Wireless tower down, 8,000 subscribers calling. Fiber cut during construction, entire business park dark.
Telco Bill Inquiries: An AI-First Approach
Bill inquiries are the single largest inbound call category at every major telecom carrier. "What's my bill? When's it due? What's this charge?" — these calls are high-volume, structured, and mostly automatable.
Onboarding SaaS Customers with Voice Agents
SaaS onboarding is the single most predictive period for long-term customer value. Customers who activate quickly, see value in their first week, and set up their integrations properly renew and expand.
Returns and Refunds via Voice Agent: A Playbook
Returns and refunds are the second-biggest voice AI opportunity in e-commerce after order status. Every retailer processes thousands of return requests per month, each call following a predictable pattern, each eating 3–5 minutes of a human agent's time, and each one carrying…
Order-Status Voice Agents: The Quickest E-commerce Win
If you run an e-commerce business and you haven't deployed voice AI for order-status inquiries, you're leaving the easiest ROI on the table. Order-status calls are the single largest inbound volume bucket for most retailers.
How Healthcare Providers Use Voice Agents for Intake
Patient intake is one of the most repetitive, error-prone, and staffing-intensive workflows in healthcare. Every new patient, every annual physical, every specialist visit triggers the same set of questions: insurance verification, medical history, reason for visit, medications,…
How AI Receptionists Coordinate with Calendars
A receptionist that can't see the calendar is just a voicemail with better diction. The moment an AI agent can actually read availability, book appointments, reschedule, and cancel — against a live scheduling system — it becomes genuinely useful.
Cost Comparison: Hiring a Receptionist vs Deploying AI
Every practice manager, office administrator, and small-business owner has a version of this math on their whiteboard: the front desk is stretched thin, we need more coverage, do we hire another receptionist or try one of these AI voice things?
How AI Receptionists Handle Repeat Callers
Every repeat caller is an opportunity to either delight or annoy. A returning patient who's had to re-explain their situation for the fifth time this year has been trained to hate your phone system.
When to Hand Off to a Human Receptionist
The single biggest quality dimension of an AI receptionist isn't how well it handles calls — it's how cleanly it hands off the ones it shouldn't handle. A competent AI with a smooth escalation path beats a great AI with a crappy one every time.
Voicemail Replacement: Why AI Receptionists Win
Voicemail is the most common front-door experience in small business. It's also the worst one. Callers hate it. They forget what they wanted to say, stumble through the message, and hang up.
Appointment Booking via Voice Agent: A Complete Guide
Appointment booking is the single most common workflow for AI voice agents across verticals — dental, medical, legal intake, service businesses, hotels, salons, veterinary.
How AI Receptionists Should Handle Emergencies
Every AI receptionist you deploy will eventually take an emergency call. A patient having a stroke. A property tenant with water gushing through the ceiling. A law-firm client who was just arrested.
After-Hours Coverage with AI Receptionists
After-hours is almost always the first place to deploy an AI receptionist. The comparison point is brutal: most teams' current after-hours handling is a voicemail box that gets checked at 9 AM the next day, and a 30% callback rate.
Multi-Department Call Routing with AI Voice Agents
Most organizations of any size have the same front-door routing problem: one main number, many departments, and an IVR tree that callers hate navigating. "Press 1 for sales. Press 2 for support. Press 3 for billing.
AI Receptionists for Hotels and Hospitality
Hotel front desks deal with an unusual call mix: 30% routine (hours, directions, Wi-Fi password), 30% reservations, 20% in-stay guest requests (towels, room service, maintenance), 10% complaints, 10% everything else.
AI Receptionists for Dental Practices
Dental practices are arguably the best first AI-receptionist deployment of any healthcare vertical. Call volume is high, calls are repetitive (appointments and insurance, then everything else), the scope is bounded, and the cost per missed call is measurable — a missed…
AI Receptionists for Law Firms
Law firms lose new-client revenue every day to missed calls. A personal-injury firm that answers a new-client lead call within 60 seconds converts at 3–5x the rate of a firm that returns voicemail the next morning.
AI Receptionists for Healthcare Clinics
Healthcare clinics have the highest-value, most-underserved front-desk load in the economy. A mid-sized clinic takes 200–500 calls a day, most of which are routine: appointment booking, prescription refill requests, insurance questions, directions, intake questions for new…
When AI Should Book Meetings vs Hand Off to Humans
Every inbound call that qualifies runs into the same decision: should the AI book a meeting and end the call, or should it warm-transfer to an AE right now? The answer depends on caller intent, AE availability, deal size, and the overall strategy.
Multilingual Lead Qualification: A Practical Guide
If your business serves any US market, a meaningful share of your inbound leads speak Spanish. In some markets, it's a majority. Similar stories play out globally. Human multilingual qualification capacity is capped by hiring — bilingual SDRs are scarce and expensive.
Inbound Voice for Trade Shows and Events
Trade shows and events generate call volumes most companies aren't structured to handle well. A booth brings 300 leads in three days. A webinar brings 500 registrations in an hour. A podcast sponsorship delivers spikes when the episode drops.
How AI Agents Should Handle Pricing Questions on Inbound Calls
"What does it cost?" is the most common objection on inbound sales calls. Handled well, the question is a buying signal — the caller's thinking about actually purchasing. Handled poorly, it's where the call dies.
Lead Qualification for High-Volume Marketing Channels
High-volume paid channels — search ads, social, podcast sponsorships, direct-response campaigns — can flood a sales team with inbound calls. 500+ calls per day becomes plausible for aggressive performance marketing.
How AI Agents Handle "Send Me an Email Instead"
Every voice agent — sales, support, receptionist — eventually encounters the caller who wants to kill the conversation early with "Just email me the info." For some use cases that's the right answer. For others, it's where valuable leads go to die.
Designing Discovery Questions for AI Lead Qualification
Discovery questions are the core of qualification — the questions that surface whether a caller is a fit, how urgent they are, and what they need. In traditional sales, SDRs and AEs spend years developing intuition for which questions to ask in which order.
Inbound Voice Agents for SaaS Demos
SaaS companies traditionally run demos the same way: website form → BDR outreach → scheduled call → AE demo. Each step has friction and drop-off. Voice AI compresses the funnel: landing page "Talk to us" button → voice AI qualifies → meeting booked or demo delivered.
Using Voice Agents to Filter Out Tire-Kickers
Every sales org deals with tire-kickers — prospects who soak up AE time without any real intent to buy. Students doing research. Competitors pumping for info. People just curious. Enthusiasts evaluating with no purchase authority.
Routing Qualified Leads from AI Agents to Sales Reps
A qualified lead that doesn't land in the right AE's lap is a wasted call. Voice AI can qualify beautifully and still produce disappointing pipeline if the routing layer fails.
BANT vs MEDDIC vs CHAMP: Which Framework for AI Agents?
Sales qualification frameworks are opinions about what to ask a prospective customer to decide whether they're worth spending time on. BANT, MEDDIC, and CHAMP are the three most common, each originating in a different era and optimized for different sales motions.
Outbound for B2C: Subscription, Healthcare, and Auto
B2C outbound voice AI has different dynamics than B2B. Consumers are less forgiving of interruption. TCPA enforcement is stricter. Complaint thresholds are lower.
Outbound for B2B: Pipeline, Renewals, and Win-Backs
B2B outbound has different mechanics than B2C. Business buyers are more tolerant of outreach when it's relevant, more sensitive when it's not. Conversation quality matters more than volume.
How to Run an Outbound AI Pilot That Doesn't Embarrass You
The failure mode for outbound AI pilots isn't "it didn't work." It's "it worked badly in public." A scaled pilot that generates complaint calls, social media backlash, or a TCPA letter from a plaintiff's lawyer damages the brand in ways the pipeline it generated can't offset.
When AI Should Hand Off an Outbound Call to a Human
An outbound voice AI that never hands off is a robot that plows through every situation with the same script. An outbound voice AI that hands off too quickly is a useless layer between the dialer and the human. The right calibration sits between.
How to Coach an AI Outbound Agent Like an SDR
Human SDRs improve through coaching. You sit with them on calls, listen to recordings, mark what worked and what didn't, and iterate. AI outbound agents improve the same way — but the coaching mechanism is prompt engineering, example curation, and eval runs instead of direct…
Outbound Voice Agents for Renewal Conversations
Renewal conversations are the most overlooked voice AI opportunity in SaaS and subscription businesses. A renewal is 90% already-decided by the time it shows up on the calendar — customer experience, product value, and relationship history have already determined the outcome.
Voicemail Handling for Outbound AI Agents
Most outbound calls don't reach a person. Answer rates for cold calls hover around 10–15%; for warm re-engagement, maybe 20–30%. That means 70–90% of your outbound attempts end in voicemail.
How to Personalize Outbound Voice Agents at Scale
Personalization is the single biggest differentiator between outbound voice AI that converts and outbound voice AI that feels like spam. Generic "Hi, we have a great product" calls get hung up on.
Lead Re-Engagement Sequences with Voice Agents
Every sales team has a graveyard of leads that went cold. People who asked for a demo six months ago, got distracted, and never came back. Prospects who said "not now" that turned into "not ever." Stalled opportunities that slipped off the forecast.
How AI Voice Agents Book Meetings on Calendars
Voice agents that book meetings are handling one of the simplest-looking but most high-leverage workflows in the whole voice AI stack. The mechanics are straightforward — query availability, offer slots, confirm the booking, send notifications.
When to Use AI for Discovery Calls (and When Not To)
Discovery calls are the first substantive sales conversation with a prospect — the call where pain gets articulated, scale gets captured, and the decision process gets mapped. It's a high-stakes, high-skill conversation traditionally held by senior SDRs or AEs.
Designing Outbound Sequences That Convert
A single outbound call rarely converts on its own. The conversion happens through sequences — the choreographed series of touches across voice, email, SMS, and sometimes even direct mail that keeps a lead warm until they're ready to talk.
How AI Agents Should Handle "Not Interested"
"Not interested" is the most common response on outbound calls. How the AI handles it determines whether the call ends politely and the caller has a positive impression of your brand — or whether it ends with an irritated caller, a complaint, and maybe a TCPA claim.
Outbound AI Calling in 2026: A Practical Playbook
Outbound AI calling is both the largest opportunity and the most dangerous terrain in voice AI deployments in 2026. Done well, it drives qualified pipeline at scale, reactivates dormant customers, and handles renewal conversations that human SDRs can't get to.
How to Calculate ROI for AI Customer Support
ROI calculations for AI customer support often use the wrong baselines and the wrong metrics. The result: numbers that look great in a deck but don't match reality once deployed. The right model captures the full cost and benefit stack, including second-order effects.
Designing AI Agents That Cancel Subscriptions Honestly
Subscription cancellation is a legally loaded support interaction. Several jurisdictions now require cancellation to be as easy as signup ("click-to-cancel" laws).
How AI Support Agents Should Handle Account Verification
Account verification is where customer support meets security. Get it wrong and you've enabled social engineering attacks. Get it too strict and legitimate customers can't get help. AI agents have specific advantages and specific risks in this tradeoff.
Multilingual Support: When and How to Add a Second Language
Adding a second language to an AI voice agent feels simple on paper — the models support it, the TTS is available, switch a flag. In practice, good multilingual support is a project. Done well, it unlocks new markets. Done poorly, it confuses customers in both languages.
Voice Agent Onboarding: A 30-Day Plan for Support Teams
Most voice agent deployments fail not because the technology doesn't work but because the team isn't ready to operate it. A clean 30-day onboarding plan — covering build, test, soft launch, and full rollout — gets you from "we should try this" to "we're running real production…
Reducing Repeat Contacts with Better Knowledge Bases
Repeat contacts — when a customer comes back about the same issue — are often a knowledge base problem in disguise. The AI agent didn't have the answer the first time, so it gave a partial response, escalated, or punted. The customer comes back.
How AI Agents Coordinate with Intercom
Intercom positions itself as the "AI-first" support platform with Fin as its in-house AI agent. But many teams running AI voice or third-party AI chat agents still rely on Intercom for ticket management and customer messaging.
How AI Agents Coordinate with Helpdesks Like Zendesk
The AI agent on your phones doesn't replace your helpdesk — it feeds into it. Every call should produce a clean ticket in Zendesk (or whatever helpdesk you use) with the right context, intent tags, and follow-up actions.
Self-Service vs AI-Assisted Support: A Decision Framework
For any support interaction, you have three options: let the customer self-serve via help docs, let an AI agent handle it conversationally, or route to a human. Each has different costs, different success patterns, and different fit.
Designing Voice Agents for After-Hours Support
After-hours coverage is often the easiest, highest-ROI first deployment for AI voice agents. Most companies' alternative is a voicemail box that doesn't get listened to until morning.
When to Let an AI Agent Apologize (and When Not To)
Apologies from AI agents are a small but loaded design decision. Over-apologize and the agent sounds insincere — performative empathy that customers see through. Under-apologize and the agent comes off as cold or evasive.
Cutting Average Handle Time with Voice Agents
Average Handle Time (AHT) is a contact-center fixation that doesn't always serve customers. AI agents can crush AHT by being faster than humans on routine tasks — but optimizing for AHT alone can hurt the things that actually matter.
How AI Agents Should Handle Angry Customers
Angry customers are the highest-stakes interactions in support. The AI's response in the first 10 seconds determines whether the call recovers or escalates into a complaint.
How AI Agents Handle Multi-Step Account Issues
Single-intent calls are the easy case for AI customer support. The hard case is when one call spans multiple related issues — a billing dispute that uncovers an address change that surfaces a misconfigured payment method.
The Anatomy of an AI-Resolved Support Ticket
What happens, end to end, when an AI agent resolves a support ticket? The full trace — from inbound call to resolved CRM record — is more interesting than most marketing materials show. Walking through a real example helps demystify what AI customer support actually does.
How to Migrate from a Legacy Contact Center to AI
Migrating from a legacy contact center (Five9, Genesys, NICE, etc.) to an AI-first stack is a real undertaking. It's not a single project; it's a 6–18 month transformation. The teams that get it right do it incrementally — one intent, one channel, one team at a time.
Designing Escalation Paths Between AI and Human Agents
The handoff between AI and human is where most "AI customer support" projects succeed or fail. A clean handoff makes the AI feel like a productive teammate. A bad handoff makes the customer repeat themselves to a human who has no context, which is worse than no AI at all.
How AI Agents Handle Refunds and Returns
Refunds and returns are where AI customer support meets real money. The agent's choices have direct cost implications. Done right, AI handles 70%+ of refunds and returns within policy, escalates the edge cases cleanly, and saves your team hundreds of hours a month.
Voice vs Chat for Customer Support: Which to Deploy First
Most teams adding AI to customer support face the same question: voice or chat first? Both make sense; both can be the right answer; the trade-offs are real. The decision should be based on where your customers actually are, not on which technology is more exciting to build.
Building a Tier-1 AI Support Agent Step by Step
Tier-1 support is the high-volume, low-complexity layer that most contact centers spend the bulk of their time on. Order status, password resets, account questions, simple troubleshooting. It's also the layer where AI has the strongest economic case.
The Definitive Guide to AI Customer Support in 2026
AI customer support has gone from "experimental" to "the default first line" in less than three years. The teams that have it working well are running 60–80% deflection rates, sub-$0.50 cost per resolution, and CSAT within striking distance of human-handled calls.
Designing Voice Agents That Ask Better Questions
A voice agent that asks bad questions wastes the caller's time and produces bad data. Good questions feel natural and capture what you need in fewer turns.
First-Time Builder's Guide to Voice Agents
Building your first voice agent is mostly about resisting the urge to overengineer. You don't need to compare 8 LLMs. You don't need to design a multi-agent architecture. You need to get a single bounded agent on the phone, listen to it talk to real humans, and iterate.
Voice Agent Use Cases: A Field Guide
The "voice AI for customer service" pitch has gotten so widespread that it's hard to remember how many specific use cases live underneath it. Some are mature and ready to deploy. Some are still painful.
Voice Agent Persona Design: A Framework
A voice agent's persona — its name, voice, tone, and conversational style — does more work than most teams realize. It sets caller expectations within the first three seconds and shapes how forgiving callers will be when things go wrong.
The Real Cost of a Voice Agent Conversation
The marketing pages will tell you a voice agent costs "fractions of a cent per minute." The reality is more interesting and more variable. Once you account for telephony, STT, LLM, TTS, and the long tail of operations, a typical 3-minute support call lands somewhere between…