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We’ve opened our AI ecosystem to partners and developers. So, here’s our practical guide to how you can go from an idea to a live integration. One that Aircall's AI agents can call on in real time—using our Developer Portal—to plan, build, and publish.
Most AI tools were built for one person at a time. You open a private chat, teach it something, and close the tab, and everything you just taught it stays with you. That model made sense when AI was a personal productivity boost.
You've been here before. The same alert fires again, the fourth time this quarter, and you're the only one who knows exactly what to run to fix it, because you're the one who figured it out during a panic-driven 3 AM call months ago.
A finance team once caught an agent approving a 40% discount [https://atlan.com/know/context-graph-vs-knowledge-graph/] for a client capped at 25%. The model sounded confident. It cited the right policy name. It was dead wrong.
A team runs an AI agent on what looks like a clean dataset and asks a simple question: what's the projected Q4 revenue for the East Coast division? The agent returns a number, confident and completely wrong. The real culprit usually isn't the model.
You've felt it. You tell Claude your product roadmap, then jump into ChatGPT to draft a launch email and realize it has no idea what you're talking about. The knowledge you painstakingly built in one tool is completely absent in another.
Your team lives in Slack. Your answers live in a warehouse, a CRM, and a dozen other SaaS tools that don't talk to each other. So people toggle tabs, copy-paste numbers into a channel, and hope the figure they just posted is still current by the time someone reads it.
Introduction You know that feeling of dread when someone asks a question you know is answered in that doc you wrote six months ago? The doc that’s now riddled with stale screenshots and outdated numbers. Traditional wikis rot.
Will AI replace customer service jobs? BLS, Gartner, and PwC data on which tasks go, which grow, and what the retrained role pays.
AI has radically changed search and SEO. Since launching 2 years ago, Google’s AI...
A researched map of how teams watch AI agents calling REST and general APIs in 2026: the application-layer trace platforms, the API-gateway layer where identity actually lives, and what genuine per-agent attribution requires.
MongoDB Field CTO Pete Johnson traces the company's shift from lexical to vector and hybrid search, new $rankFusion and $rerank query stages, and the Voyage AI acquisition's contextualized chunking and embedding techniques.
Generalist AI is the first company to demonstrate clear scaling laws in robotics, with its GEN-1.5 model continuing to show smooth performance improvements after eight months of pretraining. Last week, Radical portfolio company Generalist AI released its latest robot foundation model, GEN-1.5.
Claude, ChatGPT, and Gemini can all build an app inside the chat. The question nobody answers is what survives when you close the tab, or when the builder shuts down.
Ongoing cost, sovereignty, and security issues that arise as enterprises move from experimentation w ...
The YC S26 Startup Radar from Vela, a tier-1 quant VC. All 122 B2B companies in the YC Summer 2026 batch scored with quantitative models and two taste profiles, Vela's own and one built from the public track record of a16z, a tier-1 VC. Filter, sort, and decide who to meet first.
For a decade, Aircall has connected businesses to the tools their teams run on. Today, that same ecosystem opens to AI, giving partners and developers a public, documented path to build voice and messaging agents and to connect their own systems to Aircall's AI.
Compare 10 AI copilots and agents for ad creative in 2026 to analyze, generate, and fix ads, with pricing, ratings, and where Segwise best fits your team.
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