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Just as enterprises continue to adopt large language model-powered text-to-SQL as a way to ‘talk’ to their data assets, a new shift in the ecosystem has started emerging: AI agents. Today, New York-based Redbird announced a new chat platform that uses “specialist agents” to help enterprises handle most analytics value chain tasks, from data collection and engineering to data science and producing actual insights (reporting).
This means an enterprise user can give a natural language prompt to get insights from data in almost real-time and execute analytical efforts that pave the way for those insights. According to Erin Tavgac, the co-founder and CEO of the company, this represents more than 90% of an enterprise’s business intelligence efforts.
“For the past several decades the promise of truly self-serve analytics has fallen short for organizations, with the reality instead being complex data pipelines, dashboards, and shadow analytics that require technical skills. We have invested significant R&D into fusing the power of LLMs with Redbird’s robust end-to-end analytical toolkit in the form of AI agents that enable users to finally achieve self-serve, conversational BI that runs on their organization’s data,” he said in a statement.
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Moving into the age of AI agents
While the age of AI agents is new, Redbird itself has been a long-standing player in the analytics domain. The company started in 2018 as Cube Analytics and provided enterprises with a no-code, drag-and-drop toolkit that enabled their users to create workflows aimed at automating and unifying all analytical tasks leading to dashboarding and insights. Earlier this year, the company expanded this work with the launch of a conversational interface, allowing users to ask business questions in natural language and receive insights and reporting outputs in real-time.
Now, as the next step, Redbird has added an ecosystem of specialized agents that operate on top of this end-to-end toolkit to orchestrate as well as execute multi-step analytical tasks to answer business-related questions.
As Tavgac explained, admins setting up the chat platform have to choose a base LLM (like GPT, Llama etc) and load up their organization’s proprietary data ontologies, business logic and reporting blueprints (like business definitions, PowerPoint report templates, etc.) to customize it with relevant business context. Once the data is inputted, the AI agents using the LLM begin to use all the context and generate metadata from the information to do their work — in response to user questions.
“User prompts are sent to Redbird routing agents, which identify the best specialist agents to execute the tasks for that prompt (like PowerPoint Reporting agent, Data Engineering agent, etc.) and figure out how to orchestrate the execution order of those agents. Each specialist agent then manages its own part of the overall task by identifying relevant datasets/ontologies and executing the needed task using the Redbird toolkit, which includes applications and functions to handle the mechanical steps of the pipeline,” Tavgac noted.
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Detailing the tasks, he noted Redbird agents can pull unstructured or structured data from over 100 data sources, including Snowflake, Databricks and Hubspot. It can run advanced processing on top of the collected data by performing data wrangling, AI-driven tagging and data science modeling. It can also generate robust reporting outputs (like presentations, Excel reports and email/Slack updates) while taking necessary actions based on those reports (like executing an ad buy/modifying a campaign).
“Once the task is executed, the chat platform responds to the user with not just a text answer but also any deliverables needed, like a PowerPoint report the agents built or the data that they collected from a SaaS system,” he said.
Redbird Platform Screenshot – AI Chat (Marketing Analytics)
No-code workflow orchestration remains available
As enterprises double down on their data efforts, going beyond text-to-SQL — adopted by Dremio, Snowflake and many others – and streamlining the analytics pipeline end-to-end with AI agents could be a great way to save time and resources.
However, as many may still have concerns over the reliability of AI agents, Redbird is not doing away with its original drag-and-drop interface for automating business intelligence workflows. Instead, the company has made no-code the secondary option for users. The agents will orchestrate the tasks while also creating a no-code version of the workflow, allowing users to audit and inspect everything in detail if required.
“So far, existing AI solutions have primarily tackled the automation of a very small fraction of BI and analytics efforts (SQL querying). While Redbird values and solves for that use case (text-to-SQL), it is also applying the power of its AI agents to automate the other more difficult and more sizable parts of enterprise BI workflows… Our approach to solving this challenge has enabled us to onboard eight of the Fortune 50 brands and over 30 mid-to-large-sized enterprise customers in the last few months,” Tavgac added. This includes brands like Mondelez International, USA Today, Bobcat Company and Johnson & Johnson.
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Currently, he said the company is offering its technology on a SaaS model with usage-based licensing fees and generating seven-figure revenue. However, he did not share the exact specifics.
As the next step, Redbird will continue its AI agent-driven work and take its new Chat platform to more enterprises. It also plans to add more advanced agents in the analytics value chain to enable even deeper AI-powered business intelligence coverage for non-technical users.
“We also aim to expand beyond our primary focus on analytics / BI use cases and into a deeper ‘Large Action Model’ approach that leverages AI agents that can take more nuanced action based on the analytical results (i.e. purchase supplies, send invoices).
VB Daily
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You know how Marvel and DC have held joint ownership over trademarks for “Super Hero” for decades? That time is apparently mostly over, as the US Patent and Trademark Office has canceled the companies’ claim to several of their trademarks, reports Reuters.
The cancellation comes as the result of a challenge from Superbabies Limited, a small company that produces a series of Superbabies comics about, well, superhero babies. Superbabies creator S.J. Richold decided to challenge the two comic giants’ claim to the trademarks after DC “attempted to block Richold’s efforts to promote The Super Babies,” wrote the law firm that represented Richold in a release.
Marvel and DC didn’t respond to the challenge by a July 24th, 2024 due date, resulting in the marks’ cancellation, according to the USPTO’s decision. As such, the office canceled four patents, the oldest of which USPTO records show was for the trademark “SUPER HERO,” registered in 1967. The two companies still co-own a “SUPER HEROES” trademark, registered in 2018, as well as a “SUPER-VILLAIN” trademark that they secured in 1985.
If you want to dive down a rabbit hole on the subject of Marvel and DC’s super hero-related trademarks, I’ve got just the thing. One of the lawyers involved in the Superbabies trademark challenge, Adam Adler, actually wrote up a two-part series of articles for Escapist Magazine lightly explaining how the companies came to jointly own the trademarks and what they’ve done to guard that ownership over the years. Adler links out to other articles with even deeper dives, too.
As spotted by SamMobile, the exact text reads: “Fees may apply to certain AI features at the end of 2025.” That’s not particularly specific or definitive, but it does suggest that the Galaxy AI experience isn’t going to be completely free beyond the end of next year.
This isn’t new: the same disclaimer was included in the information we got alongside the Samsung Galaxy S24 series at the start of this year. This isn’t a surprise then, but it shows Samsung hasn’t changed its plans for charging for AI.
We don’t yet know which features might come with a price tag attached, or what that price tag might be – Samsung hasn’t said anything about that yet, but has gone on the record to say more Galaxy AI features are on the way.
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The cost of AI
ChatGPT has a paid-for tier (Image credit: OpenAI)
It’s not a huge shock that Samsung wants to start making some money from all the AI tools it’s stuffed into its devices: generative artificial intelligence requires a huge amount of computing power, and a huge amount of energy to run.
Both Google and OpenAI, the developer of ChatGPT, offer users more advanced features and more powerful AI models for $20 (about £15 / AU$29) a month – although there are rumors that the price of ChatGPT Plus could more than double in the next five years.
Then there’s Apple: Apple Intelligence is rolling out over the next few months, free of charge, but there has been talk that more advanced features are eventually going to have a price attached, perhaps as part of an Apple One bundle.
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For now, you can still use the AI features – covering image editing, live translation, note summaries, and plenty more – free of charge. If you start to reply on them regularly though, bear in mind that there might eventually be a cost attached.
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A smiling face made from living human skin could one day be attached to a humanoid robot, allowing machines to emote and communicate in a more life-like way, say researchers. Its wrinkles could also prove useful for the cosmetics industry.
The living tissue is a cultured mix of human skin cells grown in a collagen scaffold and placed on top of a 3D-printed resin base. Unlike previous similar experiments, the skin also contains the equivalent of the ligaments that, in humans and other animals, are buried in the layer of tissue beneath the skin, holding it in place and giving it incredible strength and flexibility.
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Michio Kawai at Harvard University and his colleagues call these ligament equivalents “perforation-type anchors” because they were created by perforating the robot’s resin base and allowing tiny v-shaped cavities to fill with living tissue. This, in turn, helps the robot skin stay in place.
The team put the skin on a smiling robotic face, a few centimetres wide, which is moved by rods connected to the base. It was also attached to a similarly sized 3D shape in the form of a human head (see below), but this couldn’t move.
“As the development of AI technology and other advancements expand the roles required of robots, the functions required of robot skin are also beginning to change,” says Kawai, adding that a human-like skin could help robots communicate with people better.
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A 3D head shape covered in living skin
Takeuchi et al. (CC-BY-ND)
The work could also have surprising benefits for the cosmetics industry. In an experiment, the researchers made the small robot face smile for one month, finding they could replicate the formation of expression wrinkles in the skin, says Kawai.
“Being able to recreate wrinkle formation on a palm-sized laboratory chip can simultaneously be used to test new cosmetics and skincare products that aim to prevent, delay or improve wrinkle formation,” says Kawai, who performed the work while at the University of Tokyo.
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Of course, the skin still lacks some of the functions and durability of real skin, says Kawai.
“The lack of sensing functions and the absence of blood vessels to supply nutrients and moisture means it cannot survive long in the air,” he says. “To address these issues, incorporating neural mechanisms and perfusion channels into the skin tissue is the current challenge.”
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