Jedify 正式发布 Data Agents 用于以通俗语言建设AI分析器
企业人工智能背景启动Jedify Inc. 今天正式的发布 Data Agents，这个产品让商业团队通过描述他们想要用平通语言完成的工作来建立自主的AI分析。
数据Agents对商业智能软件有着长期的限制，分析人员必须先于时间围绕他们期望人们提出的问题来建立仪表板。 通用AI助手试图填补这一空白。 Jedify说，这些工具最终会猜测其原始桌子和图谋意味着什么。
公司的核心产品是一个上下文图，将结构化的数据和文档拉入一个单一的模型，说明企业是如何运作的，下至度量定义和记录级权限。 数据Agents运行于上。 由于加入和生平图已经在图中绘制出，因此建筑agent下架来描述这个问题。
用户决定agent运行的时间，无论是应请求运行，还是按时间表运行，还是满足他们定义的条件。 一个开始表现不佳的市场是那种不正常的agent是用来自己捕捉的，杰迪菲的深层研究引擎随后就研究出最有可能驱动变化的东西。
数据访问与提问的人有关。 agent的结果中，在成本方面，Jedify 声称其agents的每个问题所燃烧的活字符号远少于在查询时间必须去探索生字图的活字符号。
团队也可以在Jedify自己的接口外与agents合作。 根据"模型上下文协议"，每个都作为工具出现，可以从公司运行的Claude,ChatGPT,Slack或任何agent平台上调用。 结果也可以直接转到电子邮件或Slack.
Jedify在数据组和他们所支持的业务人员中投出产品，认为不断出场相同的仪表板请求的分析人员可以将其交给agent. 在商业方面，从事金融，收入业务和销售的人可以自行设立agents.
联合创始人兼首席技术官Adi Elimelech 称企业正在“从回答问题到开展有意义的工作”的分析。 称的目标是，各小组建立一支与其业务运作方式相匹配的“分析队伍”，并从雇员已经使用的工具中达到agents。
在线赌场游戏开发商RubyPlay有限公司已经在使用该产品。 它的团队将agent设置一次，并安排它每天运行，现在的报告到达时没有人要求。
称 Avi Baruch是RubyPlay的数据和商业应用副总裁。
数据Agents现在可以通过Jedify的Agents枢纽获得，公司可以免费开始使用。 Jedify是一个由风险资本支持的起步企业，拥有超过3300万美元的融资，包括由Norwest在6月牵头的2400万美元的A系列。
图片：Jedify
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Jedify formally launches Data Agents for building AI analysts in plain language
Enterprise artificial intelligence context startup Jedify Inc. today formally launched Data Agents, a product that lets business teams set up autonomous AI analysts by describing the work they want done in plain language.
Data Agents takes on a longstanding limit of business intelligence software, where analysts have to build dashboards ahead of time around the questions they expect people to ask. Generic AI assistants have tried to fill that gap. In Jedify’s telling, those tools end up guessing at what a business means from its raw tables and schemas.
The company’s core product is a context graph that pulls structured data and documents into a single model of how a business works, down to metric definitions and record-level permissions. Data Agents runs on top of it. Because joins and schema mapping are already worked out inside the graph, building an agent comes down to describing the question.
Users decide when an agent runs, whether on request, on a schedule or when a condition they have defined is met. A market that starts to underperform is the kind of anomaly an agent is meant to catch on its own, and Jedify’s deep research engine then works out what most likely drove the change.
Data access is tied to the person asking the question. Anything that user is barred from seeing, even a single row in a table, stays out of the agent’s results. On cost, Jedify claims its agents burn far fewer tokens per question than ones that have to explore raw schema at query time.
Teams can also work with the agents outside Jedify’s own interface. Under the Model Context Protocol, each one appears as a tool that can be called from Claude, ChatGPT, Slack or any agent platform a company runs. Results can go straight to email or Slack too.
Jedify is pitching the product at data teams and the business staff they support, arguing that analysts who keep fielding the same dashboard request can hand it off to an agent. On the business side, people in finance, revenue operations and sales can set up their own agents.
Co-founder and Chief Technology Officer Adi Elimelech said enterprises are moving analytics “from answering questions to doing meaningful work.” The goal, he said, is for teams to build “an analytical workforce” matched to how their business operates and reach those agents from the tools employees already use.
Online casino game developer RubyPlay Ltd. is already using the product. Its team set an agent up once and scheduled it to run every day, and the report now arrives without anyone asking for it.
“It even flagged us on its own that not all of our target markets were covered yet, which told us it was reasoning through the task rather than just running a script,” said Avi Baruch, vice president of data and business applications at RubyPlay.
Data Agents is available now through Jedify’s Agents Hub, and companies can start on it for free. Jedify is a venture capital-backed startup that has raised more than $33 million, including a $24 million Series A round led by Norwest in June.
Image: Jedify
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