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What's Acela Tech trading at right now, and any news I should know about?

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ACLT is at $184.20, up 1.4% today. Recent headlines: a new data-center chip announced this morning, a Meridian Capital upgrade, and continued coverage of supply constraints. Want me to dig into any of these?

Run the technicals on it.

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On the daily: price is above its 50- and 200-day moving averages, RSI is 68 (nearing overbought), and it's testing resistance around $186. MACD is positive but flattening. For context, not a recommendation, that mix often points to a stock that's extended after a strong run.

Rasa provides a patented dialogue management system designed for enterprise AI agents. It orchestrates autonomous reasoning, guided workflows, and shared conversational memory within a builder-friendly architecture.

Teams can design, test, and refine complex conversational logic while maintaining transparency and control, enabling agents to reliably support structured business processes and adapt to real-world interactions.

Deploy Rasa on your own infrastructure, private cloud, or fully offline environments—including air-gapped deployments when required. Organizations retain full control over their data, security, and model providers.

Built with regulated industries in mind, Rasa enables teams to meet strict compliance and governance requirements without sacrificing flexibility in infrastructure, integrations, or AI model choice.

Rasa enables organizations to coordinate multiple AI agents across systems and workflows. Agents can share conversational state, access unified memory, and hand off tasks seamlessly between domain-specific skills.

This architecture allows teams to start with a single production agent and scale to a distributed network of enterprise agents without redesigning their underlying conversational infrastructure.

Built on open principles and inspired by its open-source roots, Rasa provides full access to prompts, policies, and the underlying codebase. Teams can choose their preferred LLMs, infrastructure, and integration layers without vendor lock-in.

This flexibility allows organizations to adapt the framework to evolving requirements while maintaining full visibility and control over their AI systems.

Rasa supports real-time voice interactions designed for natural, human conversation. Low-latency processing enables streaming speech recognition, fast turn-taking, and responsive dialogue flow across phone and voice channels.

The system supports core voice primitives such as barge-in, turn-taking, and background noise handling, allowing AI agents to manage interruptions, respond quickly, and sustain fluid back-and-forth conversations.

Rasa provides built-in tools to monitor, evaluate, and improve AI agent behavior in production. Teams can trace conversations, inspect decision paths, and analyze workflow performance to quickly diagnose issues.

With transparent logs, evaluation tools, and feedback loops, organizations maintain operational oversight while continuously optimizing agent reliability, safety, and business impact.

1: Build your conversational voice or chat agent in our open developer framework using our coding copilot to accelerate development and follow best practices.

2: Deploy your Rasa Agent on your own infrastructure while Rasa orchestrates conversations, guided flows, external agents, and knowledge retrieval.

3: Refine your agent in Rasa Studio to optimize the experience and track performance across channels and modalities.

We've built a scalable, compliant platform with Rasa that supports real patient needs and drives measurable outcomes. CALM gives us a framework to keep that momentum going, with the flexibility to grow responsibly as expectations around AI continue to evolve.

Wayne Foley

Director Software Engineering, Digital Innovation Group, at Providence

With Rasa, we launched quickly and gave citizens a simpler way to access government services. The system allows us to expand at our own pace while controlling how services are delivered. Studio and CALM allow us to build new use cases while maintaining stability as the platform grows.

Bogdan Stešević

Head of the Group for Quality of Services and Development of AI at eUprava

We’re not experimenting with voice. We’re deploying it. That’s the difference.

Loic Mayet

Information Systems Director, Groupe IMA

Switching to Rasa accelerated development. We now process thousands of conversations each month with 96% accuracy, which resulted in better user engagement and more searches per conversation.

Edmundas Balčikonis

CEO, Eddy Travels

We developed a real partnership with Rasa based on developing skills rapidly, correcting bugs quickly, and sharing a wish list with the dev team.

Richard Popa

Project Leader and Solutions Manager, Orange

Albert Heijn adopted Rasa and began migrating to CALM through a coexistence strategy — starting with a single flow and gradually expanding coverage, achieving a 22% improvement in prevented contact rate and a 37% increase in quality score.

Albert Heijn

Largest supermarket chain in the Netherlands

Grace acts as a multi-purpose patient-facing assistant — booking appointments, routing based on symptoms, and helping users navigate their care journey entirely through our app.

Providence Health

Digital Innovation Team

With Rasa, we consolidated five bots into a single assistant experience. Fallback rates dropped from 18% to 3.5%, and we’re now expanding to voice.

nib Group

Digital Team Lead

N26 transitioned from concept to production in just four weeks, deploying the AI assistant within their secure cloud environment to maintain full data control.

N26

Rasa’s platform enabled us to customize and scale our AI assistant’s capabilities, ensuring it evolved with changing member needs and organizational goals.

nib Group

With Rasa, we at ERGO are completely rethinking how we build customer support experiences. It’s about developing faster and cheaper, and at scale. Rasa helps us to realize these goals.

Gregor Wiest

Head of Innovation, ERGO Group AG

Since the chatbot based on Rasa CALM can process around 50% of service desk inquiries independently, we reduced the need for human agents by approximately 30%. Thanks to the excellent backend integration capabilities of the Rasa solution, we quickly implemented the chatbot’s self-service features.

Roland Csibi

Service Hub Owner – User Support Service Hub

Our goal was to align cutting-edge AI technology with customer needs to provide seamless and innovative experiences. Partnering with Rasa allowed us to rethink how conversational AI could transform support.

Daniel Schupmann

Head of CAI/ GenAI @B2C and Digital Care Platforms/ Experience

We needed a solution that could scale with our ambitions. Rasa solves some hard problems related to conversational AI that enable us to move faster.

James Bradley

Senior Director of Data Science & Machine Learning

impact

Building with high trust

agents drives results

50%

Cost reduction in operational expenses across 50+ enterprise deployments

59%

Goal completion rate per conversation

4.4

Star customer satisfaction consistently maintained