Der Sierra-Blog

25. März 2026

Agents as a Service

Sierra is reimagining software for the agent era—where you simply describe the outcome, and intelligent agents build, execute, and continuously improve the work for you. Meet Ghostwriter, the agent that creates and optimizes other agents, turning your ideas into production-ready customer experiences without clicks, code, or complexity.

6. Februar 2026

Year two in review

Sierra is heading into year three with over $150M in ARR, powered by rapid adoption from some of the world’s largest companies. The growth reflects a simple idea: when AI is built around real jobs to be done (not experiments), even the biggest enterprises can see meaningful impact fast.

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5. November 2025

Sierra Agent OS 2.0: from answers to memory and action

At Sierra Summit, we unveiled the future of AI agents: a single agent that works across every channel, learns from every interaction, and builds real customer relationships. With eight new products, including Agent Studio 2.0 and the Agent Data Platform, Sierra is turning the promise of AI-powered customer experience into reality.

5. November 2025

Introducing Agent Data Platform

Sierra’s first-of-its-kind Agent Data Platform (ADP) gives agents memory, context, and intelligence — turning every interaction into a human, personalized experience. Powered by Agent OS, ADP helps companies move from answering questions to anticipating needs.

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𝜏-knowledge: benchmarking agents on real-world knowledge

𝜏-Knowledge measures how well agents can work through messy, evolving knowledge bases to complete complex, multi-step tasks. While models are improving, they still struggle to reliably use this information in practice, leaving a large gap to real-world performance.

13. Mai 2026

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Who monitors the monitors?

Sierra's always-on evaluation layer use an LLM-as-judge to review every conversation so businesses can track agent quality and customer sentiment. But who evaluates the monitors?

7. Mai 2026

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Kontext-Engineering: der Schlüssel zu hervorragenden Agenten

LLMs zur richtigen Zeit mit dem richtigen Kontext zu versorgen, ist die zentrale Herausforderung bei der Entwicklung ausgefeilter Agenten für die Praxis. Die Lösung: Context Engineering.

5. Mai 2026

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𝜏-voice: benchmarking real-time voice agents on real-world tasks

𝜏-voice is a benchmark for real-time voice agents on 278 grounded customer-service tasks across retail, airline, and telecom. It pairs deterministic, end-to-end task scoring with realistic, controllable audio — diverse personas, environmental noise, and free-form turn-taking.

1. Mai 2026

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Das KI-gestützte Vorstellungsgespräch

Wir haben unseren technischen Bewerbungsprozess von Grund auf überarbeitet.

22. April 2026

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μ-Bench: an open multilingual transcription benchmark

μ-Bench is an open multilingual transcription benchmark built from customer service phone calls across five locales. It aims to measure transcription providers on the errors that matter in production: not just how closely transcripts match their reference, but whether they preserve the speaker’s intent.

20. April 2026

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Golden articles: Evaluating and improving search

Search evaluation shouldn’t be static — it should reflect what actually helps resolve real customer issues. By measuring performance daily against production conversations and feeding those signals back into the system, we've built a continuously improving system for resolving customers’ needs.

14. April 2026

Meet Linnaeus and Darwin: Search models that drive higher resolution rates

Our purpose-built retrieval and reranking models outperform off-the-shelf ones, driving up to 16 percentage point improvements in resolution rates.

3. April 2026

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𝜏³-Bench: Advancing agent benchmarking to knowledge and voice

𝜏³-Bench is here. We've expanded agent evaluation to two new frontiers: knowledge retrieval and voice.

18. März 2026

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