AlphaSense has been named the only Leader in The Forrester Wave™: Market And Competitive Intelligence Platforms, Q3 2026. We received the highest possible score across 14 criteria including Accuracy and Relevancy, Vision, Innovation, Roadmap, and AI Agents. For us, this recognition reflects what our decision-grade AI platform delivers: automating the entire research process from discovery through deliverables, automated 24/7 market monitoring and centralized access to premium financial, market, expert and internal content in one unified AI platform. Access the full Forrester Wave report to see why "AlphaSense has played a dominant role in the market with its vision of marrying premier and exclusive content with domain-specific AI for an end-to-end intelligence and decision-support platform."

Exclusive: AlphaSense's revenue climbed 40% over the past year to more than $700 million in annual recurring revenue as it takes steps toward an IPO. Investors are watching whether proprietary financial data gives it an edge over foundation model companies. Details:

✨ Employee Spotlight: Meet Richard Lu! Richard Lu is a New York-based Senior Software Engineer on the Search Infrastructure team at AlphaSense, where no two days look quite the same. Mornings are anchored by syncs with a global team, and afternoons open up into flexible, focused build time. He splits his week between home and the New York office, finding a rhythm that works for him. What drives him is impact, and the ability to see it quickly. Right now that impact is showing up on SuperAnalyst, our always-on AI agent. "Not only do I get to see it being developed from 0 to 1, but I also see the changes that it goes through. I'm probably more excited about this product than any other product I've developed over the last handful of years." Thinking about joining us? Explore current openings and learn more about our company culture on our #careers# page.

A great insight means nothing if it never makes it into the deck or model that reaches leadership. AlphaSense now meets you where that work happens. Start in Generative Search to turn a question into a deliverable in your firm's template. Move into PowerPoint to drop charts, data and commentary onto slides from the sidebar, then refresh numbers or duplicate for the next company without rebuilding. In Excel, describe what you need in plain language and pull financials straight into your sheet with a clear line back to every source. See how to go from first draft to polished deck to trusted model without leaving the tools you already use. Watch now ⤵️

Every few weeks, a new model tops a public leaderboard. But in finance and business research, the model isn't the bottleneck anymore. Context is. Continuous benchmarking at AlphaSense shows GPT-5.6 Sol leading the pack, Opus 5 underperforming its predecessor at 5x the cost, and Gemma 4-31B matching Sonnet 5 quality at 40x lower cost. The lesson: newer isn't automatically better, token price doesn't equal question cost, and per-task model routing beats any single-model strategy by 2.8x. Chris Ackerson and Daniel Campos break down what months of head-to-head model testing reveal about frontier AI, and the two engineering programs designed to widen the gap even further. Read the full article:

SpaceX's IPO reopened the mega-cap tech window, and Anthropic, Databricks and Stripe are the next names on the list. But the setup is more complicated than the headline suggests. 43% of H1 2026 venture capital went to just two companies. Frontier labs are burning billions but growing rapidly. Physical AI is drawing capital fast, but full-scale deployment is still years away. HBM and optical networking are already sold out through 2028. Michelle Brophy and Sean Carmichael from AlphaSense break down the mega-cap tech IPO landscape alongside Sacra's Marcelo Ballvé and Capital Allocators' Ted Seides. ⬇️