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Thinkific Announces New Automatic Share Purchase Plan

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2 years ago

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VANCOUVER, BC, Aug. 12, 2024 /CNW/ – In connection with the Normal Course Issuer Bid (“NCIB”) previously announced on November 10, 2023, Thinkific Labs Inc. (“Thinkific” or the “Company”) (TSX: THNC), a leading platform for creating, marketing and selling online learning products, announced that it has terminated the automatic share purchase plan (the “Existing ASPP”) previously entered into with Cormark Securities Inc. (the “Broker”) and established a new automatic share purchase plan (the “New ASPP”) with the Broker.

Under the New ASPP, the Company has authorized the Broker to purchase Subordinate Voting Shares of the Company (each, a “SVS”) under the NCIB during blackout periods implemented under the Company’s Insider Trading Policy (“Blackout Periods”) and outside of Blackout Periods only when instructed by the Company from time to time during the term of the New ASPP. The New ASPP will terminate on November 8, 2024, or earlier if the aggregate number of SVSs purchased under the NCIB reaches the Maximum Limit (as defined below) or if the NCIB has been terminated by the Company.

Trading limits and other parameters for purchases during Blackout Periods under the New ASPP have been pre-determined between the Company and the Broker in accordance with the rules and policies of the TSX and applicable securities laws.

Under the NCIB, the Company may purchase for cancellation up to an aggregate of 2,444,358 SVSs (the “Maximum Limit”), representing approximately 10% of the public float (as defined in the rules and policies of the TSX) of the SVSs as of October 30, 2023. Under the NCIB, other than purchases made under a block purchase exception in accordance with the rules and policies of the TSX, the Company may acquire, from time to time, up to 5,296 SVSs per day on the TSX, being 25% of the average daily trading volume of the SVSs for the period from May 1, 2023 to October 31, 2023. Under the NCIB, purchases will be made through the facilities of the TSX, and/or permitted alternative Canadian trading systems, at prevailing market prices or such other prices as permitted under the rules and policies of the TSX and applicable securities laws. All SVSs purchased by the Company under the NCIB will be cancelled.

At the time of terminating the Existing ASPP and establishing the New ASPP, Thinkific was not aware of or in possession of any material undisclosed information about the Company, the SVSs or any other of its securities.

About Thinkific

Thinkific (TSX:THNC) makes it simple for Creator Educators and established businesses of any size to scale and generate revenue by teaching what they know. Our Platform gives businesses everything they need to build, market, and sell digital learning products – from courses to communities – and to run their business seamlessly under their own brand, on their own site. Thinkific’s 50,000+ active creators earn hundreds of millions of dollars in direct course, membership and community sales while teaching tens of millions of students. Thinkific is headquartered in Vancouver, Canada, with a distributed team.

This news release includes forward-looking statements and forward–looking information within the meaning of applicable securities laws (“forward-looking statements'”). Forward-looking statements are based on Thinkific’s current expectations, estimates, projections and assumptions made in light of information available to it at the time such forward-looking statements are made and considers Thinkific’s experience and its perception of trends. Forward-looking statements in this news release include statements regarding its intention to continue the NCIB, the termination of the Existing ASPP and the establishment of the New ASPP, the reasons for the NCIB, the timing and amount of purchases under the NCIB and the New ASPP and the cancellation of the SVSs purchased under the NCIB. Although Thinkific’s management believes that the assumptions underlying these statements and information are reasonable, they may prove to be incorrect. Except as required by applicable securities laws, forward–looking statements and information speak only as of the date on which they are made and Thinkific undertakes no obligation to publicly update or revise any forward–looking statement or information, whether as a result of new information, future events or otherwise.

Forward-looking statements and information are not guarantees of future performance and involve a number of risks and uncertainties, some that are similar to other companies with online learning products and some that are unique to Thinkific. Thinkific’s actual results may differ materially from those expressed or implied by its forward-looking statements, so readers are cautioned not to place undue reliance on them.

The Annual Information Form of the Company dated March 4, 2024 and other documents filed by it from time to time with securities regulatory authorities describe in greater detail the risks, uncertainties, material assumptions and other factors that could influence actual results and such factors are incorporated herein by reference. Copies of these documents are available under our profile on SEDAR+ at www.sedarplus.ca.

SOURCE Thinkific Labs Inc.

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JAMS Launches AI for Enterprise Job Scheduling: JAX and JAMS MCP, on the Model You Choose

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33 minutes ago

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July 24, 2026

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A new AI agent and an open-standard connector let IT teams query, diagnose, and manage automation in plain language, on the model they choose, with operational data staying inside their own network

LONDON, July 24, 2026 /PRNewswire/ — JAMS Software, an orchestration solution for scheduled and event-driven automation, today announced the general availability of two AI capabilities for enterprise job scheduling: JAX, an AI agent built into the JAMS Web Client, and JAMS MCP, a connector built on the open Model Context Protocol standard that brings JAMS into external AI coding tools. Both capabilities ship at no additional cost as part of JAMS Web.

Automation environments grow faster than the teams that run them. Jobs multiply across SQL Server, Azure Data Factory, Airflow, SAP, JDE, and Banner, and when one fails, finding the root cause often means searching several consoles at once, frequently outside business hours. At the same time, IT leaders carry pressure to adopt AI while staying accountable for where operational data goes. JAX and JAMS MCP close both gaps together.

Full details on how JAX and JAMS MCP work, including the control model behind every action, are available at jamsscheduler.com/product/ai.

JAX is an AI agent that runs inside the JAMS Web Client. It finds jobs, troubleshoots failures, and answers how-to questions in plain language, with each response grounded in the JAMS user guide and checked against a built-in glossary. JAX acts only when a user asks it to. Reads flow freely, and every write action pauses for the user’s explicit approval before it runs. JAX does not learn between sessions, and conversations are not retained on the server.

JAMS MCP is a connector, built on the open Model Context Protocol standard, that brings JAMS into the AI tools engineering teams already use, including Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex. Users query jobs, investigate failures, and manage runs in plain language without leaving their tool.

Both capabilities run inside the customer’s own network and act as the signed-in user, with that user’s exact JAMS permissions. There is no elevated AI account: whatever a user cannot do in the JAMS interface, JAX and JAMS MCP cannot do on that user’s behalf. Every JAX and MCP operation is recorded in its own dedicated log, and changes made through the JAMS API land in the JAMS audit trail like any other change. Customers choose their own AI model, whether a commercial provider such as OpenAI or Anthropic or a model running entirely on their own hardware, and JAMS never trains on customer data. In the current release, neither feature edits or deletes a job, folder, schedule, or agent definition. For teams that must keep operational data within a defined boundary, JAX runs on a local model entirely inside the customer’s own network, so nothing leaves at all.

“Adopting AI usually means giving something up, most often visibility into where your data goes,” said Pete Hegland, Chief Executive Officer of JAMS Software. “We built JAX and JAMS MCP so that trade does not have to happen. Every action runs as the signed-in user, every change waits for approval, and the model itself can run entirely inside your own network.”

“IT teams across the United Kingdom and EMEA tell us the same thing: they want the benefit of AI without losing sight of where their data goes,” said Greg McLaughlin, Account Executive for EMEA at JAMS Software. “JAX and JAMS MCP let them keep operational data inside their own network and still get answers in plain language. That combination is what makes this practical for the teams I work with.”

JAX and JAMS MCP are available now to all JAMS Web customers across the United Kingdom and EMEA, with no separate licence, SKU, or additional cost. AI-assisted creation of new jobs and workflows from a plain-language description is on the roadmap for a future release, gated by the same approvals and permissions as every other action.

Learn how JAX and JAMS MCP work at https://jamsscheduler.com/product/ai.

Fast facts

JAX is an AI agent built into the JAMS Web Client for job scheduling and workflow automation.JAMS MCP is a connector built on the open Model Context Protocol standard, for Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex.Both act as the signed-in user, with that user’s exact JAMS permissions, and there is no elevated AI account.Customers choose the AI model, including a local model that runs entirely inside their own network.JAMS never trains on customer data.Both are available now at no additional cost as part of JAMS Web.

About JAMS Software

Founded in 1987, JAMS Software is an orchestration solution that helps IT teams centralize, automate, and manage scheduled and event-driven jobs across complex, hybrid environments. Over 850 customers rely on JAMS to run their automated workloads. JAMS Software, LLC is headquartered at 108 Patriot Drive, Suite A, Middletown, DE 19709.

Media Contact
Bobby Schmidt, Vice President of Marketing
press@jamssoftware.com
800.261.4267

 

 

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Video: CNPC offers green chemical answer

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33 minutes ago

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July 24, 2026

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BEIJING, July 24, 2026 /PRNewswire/ — A news report from chinadaily.com.cn:

Located on the edge of the Taklamakan Desert in Northwest China’s Xinjiang Uygur autonomous region, the Tarim 1.2 MTA Phase II Ethylene Project and its supporting green and low-carbon demonstration facility of PetroChina Dushanzi Petrochemical Company, a subsidiary of China National Petroleum Corporation, are offering a new example of China’s low-carbon industrial transformation.

Watch the video to discover how CNPC is exploring a cleaner and more circular future for the industry.

View original content to download multimedia:https://www.prnewswire.com/apac/news-releases/video-cnpc-offers-green-chemical-answer-302834036.html

SOURCE chinadaily.com.cn

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Shanghai Electric showcases embodied intelligence robot matrix and AI-native smart factory solutions at WAIC 2026

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33 minutes ago

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July 24, 2026

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Featuring humanoid robots with 41 degrees of freedom, pipe‑inspection robots with ±1mm positioning accuracy, and 51 industrial‑grade AI agents

SHANGHAI, July 24, 2026 /PRNewswire/ — Operations in high-end equipment manufacturing often involve confined spaces, complex objects, and fine manipulation tasks that demand sustained and stable precision. At the recent 2026 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance (WAIC 2026), Shanghai Electric (SEHK: 02727, SSE: 601727) showcased its comprehensive portfolio of embodied intelligence solutions tailored to a range of industrial scenarios.

Themed “AI for All: Smart Squad, Shining Without Limits,” Shanghai Electric highlighted its capabilities across embodied AI robots, robot core components, and AI-native smart factory solutions, demonstrating end-to-end capabilities spanning complete robot systems, critical parts, industrial software, and smart factory architecture.

“The true value of embodied intelligence lies in understanding real industrial tasks: combining the strength, precision, and stability of machines with human experience and judgment to drive a genuine paradigm of ‘machine-assisted, human-machine collaboration,'” said Wang Chunlei, deputy general manager of the Robotics Business Unit at Shanghai Electric Automation Group.

Shanghai Electric’s robotics portfolio covers five key industrial scenarios: connector insertion, electrical operations, flexible sorting, intelligent assembly, and pipe processing. Highlights include:

“SUYUAN” bipedal humanoid robot: With 41 degrees of freedom for enhanced mobility, it is equipped with a multimodal visual sensing system on the head and torso, along with a dual-battery hot-swap system. It is well-suited for inspection, material handling, and assembly tasks.”TUOYUAN” industrial wheeled humanoid robot: Powered by an embodied intelligence foundation model and force-position hybrid control, it is capable of multi-spec connector insertion, material sorting, and loading/unloading of automotive sheet metal parts.”Mermaid” bionic wheeled humanoid robot: Capable of autonomously identifying buttons, knobs, and air switches, it generates real-time operation paths.Autonomous pipe inner-wall chamfering robot: Designed for confined spaces, it can position and process thousands of hole edges with accuracy within 1 millimeter while transmitting data in real time.

Shanghai Electric also showcased its portfolio of core components ranging from power-output to end effectors. Among them, the planetary roller screw offers more than three times the load capacity of traditional ball screws, while the DexHand dexterous hand is designed to meet diverse gripping and manipulation requirements.

Shanghai Electric launched 51 AI models and agents under its “StarCloud Intelligent Manufacturing” series across three domains: R&D and design, production and manufacturing, and operations and maintenance—covering critical equipment processes such as process optimization and wind power facility maintenance.

These industrial agents are embedded in robotic decision-making systems and the operational logic of AI-native smart factories, transforming industrial expertise into digitized, reusable capabilities. They support production-line scheduling, quality inspection, and predictive maintenance, driving the evolution of manufacturing systems from experience-driven to data-driven operations.

Shanghai Electric also released the “AI-Native Smart Factory Technology White Paper,” proposing an active evolution architecture that enables real‑time, closed‑loop optimization of production data, giving the factory self‑perception, self‑decision, and self‑execution capabilities. Built on First Principles, the AI‑native smart factory vertically integrates process flows, industrial software, agents, and smart equipment to dismantle traditional hierarchies while horizontally bridging data silos. The architecture features three core layers: the AI factory brain as the “control center,” industrial agents and embodied robots as the “execution network,” and the physical twin as the “digital mirror.”

Leveraging its deep industrial expertise and comprehensive solution capabilities, Shanghai Electric will continue to drive the implementation of AI in industrial settings, tackle technical challenges facing embodied intelligence in complex scenarios, accelerate the large‑scale deployment of AI‑native smart factories, and deliver replicable solutions across diverse manufacturing environments.

SOURCE Shanghai Electric

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