AI, voice agents &amp; platform engineering

Sarvam Bulbul: TTS for Indian Voices and Code-Mixing

The hardest test of an Indian-language TTS model is not pronunciation — it's a sentence like "Aap apne SBI account ki KYC pending hai, please complete it before 25 तारीख." A name, an acronym, code-switched English, a Hindi date marker, and the whole thing has to sound like a real person reading a re…

AI Phone Agents in 2026: What Businesses Are Actually Deploying

The AI phone agent went from demo to deployment between 2024 and 2026. The shift is no longer "would this work" but "where does it work, and at what cost, and how do you keep it from failing in the wild." This is what businesses are actually shipping in 2026 — separated from the louder claims. Where…

The Cost Economics of a Voice Minute in 2026

A voice minute is the smallest unit of revenue and cost for any voice AI product. Understanding what it actually costs to deliver one — and where the costs hide — is the difference between a healthy unit economics story and a graveyard of voice agent startups. Here is the 2026 breakdown. The headlin…

Emotion-Aware TTS: From Tone to Empathy

For most of TTS history, the goal was clarity. The model said the words and you understood them. By 2024 that bar was met across major languages. By 2026 the frontier has moved: TTS that does not just say the words but conveys how the words should feel. Emotion-aware TTS is the next layer of voice n…

Computer Use Agents: How They Work and What's Hard

Anthropic introduced Computer Use in late 2024 as the first production-grade API where an LLM could drive a screen — see pixels, move a mouse, type. Eighteen months in, it's no longer a research demo. Production teams are running it for QA automation, internal tooling, RPA-style workflows, and custo…

Multi-Agent Orchestration: When You Actually Need It

"Multi-agent" is the most over-applied label in the agent stack. Most production systems calling themselves multi-agent are really one capable agent with a handful of tools, dressed up. That's not a bad thing — it's usually the correct architecture. Multi-agent orchestration earns its complexity in …

AI in Customer Support: What's Actually Working in 2026

Three years after the first wave of generative AI support pilots, the customer service category looks very different from what vendor decks promised. Some deployments are quietly delivering meaningful deflection. Others have rolled back. The honest 2026 answer is "it depends on the intent shape, the…

AI for Sales Call Analysis: Real Results, Real ROI

Conversation intelligence used to be a "nice to have." In 2026 it is the default — most B2B sales orgs above 20 reps record, transcribe, and analyze every customer call. The category has matured past the demo-day pitch into something with measurable impact on win rate and ramp time. Here is what is …

AI in Healthcare 2026: Use Cases That Made It to Production

Healthcare AI in 2024 was mostly pilots. By 2026, three categories have crossed into production at scale, while several others remain stuck in the "promising but not yet deployable" bucket. Here is the working list, with HIPAA caveats called out where they apply. What made it: ambient clinical docum…

AI in Fintech: Fraud Detection and the Compliance Question

Fraud detection is the highest-volume, highest-stakes AI workload in fintech. Every card swipe, account opening, and ACH transfer in 2026 runs through a model that has milliseconds to decide "approve, decline, or escalate." The technology has matured fast — but so has regulator interest in being abl…

AI in Legal: Contract Analysis at Production Scale

Legal AI used to be the canonical "this is not going to work" category — too high-stakes, too much hallucination risk, too entrenched. Then the foundation-model wave broke through, and by March 2026 a single legal AI vendor (Harvey) was raising at an $11 billion valuation. The category is real. So i…

AI in Real Estate: Lead Qualification and Listing Generation

Real estate has spent two decades trying to fix a fundamental productivity problem: the agent's day is dominated by lead follow-up, listing descriptions, and showings logistics — none of which produce commission directly. AI in 2026 attacks the first two head-on, and the early operating data is inte…

AI Tutoring in 2026: Beyond Chat Interfaces

The first wave of AI tutoring assumed every kid would log into a chatbot, ask great questions, and get personalized instruction. The 2025–2026 deployment data tells a more complicated story: students mostly did not show up to the chatbot, and the products that work are the ones that meet learners wh…

AI in Recruitment: Resume Screening Done Right

Resume screening was one of the first AI-in-HR pitches and one of the most controversial. Amazon's discontinued screening tool, lawsuits over algorithmic bias, and a cascade of state and federal regulations have moved the conversation from "can we deploy this" to "how do we deploy this responsibly."…

AI for E-Commerce Personalization in 2026

E-commerce personalization is finally past the "show me products like the one I just looked at" era. The 2026 generation of AI personalization runs on multimodal foundation models, conversational interfaces, and a different unit of analysis: the shopper's intent rather than their click history. The …

AI in Logistics: Route Optimization and Demand Forecasting

Logistics has done operations research for fifty years. The 2026 question is not whether algorithms can route delivery vehicles — that has been a solved problem for decades. The question is whether modern AI adds enough on top of classical optimization to be worth the integration cost. The honest an…

AI Marketing in 2026: Content Generation That Converts

Three years into widespread generative AI adoption, marketing teams have lived through every possible failure mode of AI content. The early "publish 100 blog posts a week" experiments tanked traffic. The personalization-creep emails alienated lists. The AI-narrated video ads got skipped at higher ra…

AI Voice Agents for Restaurant Ordering

Drive-thru voice automation has been the most public test case for production voice AI in 2024–2026. McDonald's piloted with IBM and ended that partnership; new pilots are running with newer voice stacks; Presto raised additional capital in 2026 to scale to thousands of locations. The technology has…

AI in Insurance: Claims Processing in 2026

Insurance claims processing is one of the better-defined production AI workloads in 2026: a high-volume, document-heavy, image-heavy operation where speed and accuracy translate directly into customer satisfaction and cost savings. Lemonade processes claims in seconds. Tractable's computer vision dr…