TGM secures $35m loan agreement for South African underground gold project
The IDC has granted a seven-year debt funding loan valued at R622m ($35m) for the project, which includes an initial 18-month period where both capital and interest payments are deferred.
The agreement follows a thorough due diligence process and is subject to standard conditions including satisfactory security terms with co-lenders and completion of the company's equity funding contribution.
The company has also achieved a 13-year renewal for Mining Right 83 (MR83) until 2038. MR83 covers key mines including Beta, CDM and Frankfort within the TGME Underground gold project.
Theta Gold Mines' subsidiary has maintained control over this area for more than 130 years, underscoring its long-standing presence in the region.
Theta Gold Mines chairman Bill Guy said: 'The IDC, South Africa's state-owned institution, has completed a due diligence and approved funding of the project. Its debt funding Loan Facility Agreement in the TGME Underground Gold Project signals strong confidence in the project's economics and alignment with IDC's sustainable growth mandate.
'This is a major funding milestone, with [the] next step finalising legal agreements. IDC has a proven track record backing early-stage African successes like Kumba Iron Ore and Alphamin Resources.'
Theta Gold Mines, an advanced gold development company, is currently updating its definitive feasibility study (DFS), initially released on 27 July 2022, with the revised version expected in the third quarter of 2025.
With the current gold spot price near $3,324/oz, the updated DFS is expected to reveal substantially improved economics for the project.
Last month, the company started pre-construction at the TGME gold processing plant in South Africa.
"TGM secures $35m loan agreement for South African underground gold project" was originally created and published by Mining Technology, a GlobalData owned brand.
The information on this site has been included in good faith for general informational purposes only. It is not intended to amount to advice on which you should rely, and we give no representation, warranty or guarantee, whether express or implied as to its accuracy or completeness. You must obtain professional or specialist advice before taking, or refraining from, any action on the basis of the content on our site.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Business Wire
2 days ago
- Business Wire
Retailers Are All-In on AI - But Disconnected Data Threatens Progress
SEATTLE--(BUSINESS WIRE)-- Amperity, the leading AI-powered customer data cloud, today released its 2025 State of AI in Retail report, a new survey highlighting how retail businesses are rapidly embracing AI, but often lack the foundational data infrastructure needed to unlock its full potential. "Retailers are leveraging AI to deliver more adaptive, personalized customer experiences powered by high-quality, unified customer data,' said Tapan Patel, research director at IDC. The survey of 1,000 retail professionals across marketing, IT, data and executive leadership reveals that 45% of retailers are already using AI daily or several times per week, and 97% plan to maintain or increase their AI investment in the coming year. However, only 11% say they're fully prepared to deploy AI tools at scale. 'Retailers believe in AI's potential to drive loyalty and lifetime value — but belief alone won't close the gap between ambition and execution,' said Tony Owens, CEO of Amperity. 'What's needed is unified, actionable customer data - regardless of where it resides. With Amperity's patented identity resolution, retailers can unify data without moving it, transforming fragmented records into complete customer profiles that fuel AI and measurable business results.' Customer-Facing AI: The Missed Opportunity While 63% of retailers believe AI will improve customer loyalty and 65% expect it to increase customer lifetime value, only 43% are currently using AI in customer-facing applications such as personalization, chatbots or tailored marketing experiences. In fact, just 23% are using AI in production to resolve customer identities or prepare data for marketing use, indicating significant untapped potential in customer engagement strategies. CDPs Are Accelerating AI Maturity Retailers with a customer data cloud (CDC) aren't just slightly ahead - they're moving at a different pace entirely: 60% of CDP-equipped retailers use AI daily or several times per week (vs. 29% without a CDP) 35% use AI in production to prepare data for marketing or analytics (vs. 9% without a CDP) 22% report full AI adoption across multiple business units (vs. 10%) These retailers are also far more confident in their ability to understand and act on customer behavior, reinforcing the CDP's role as a critical enabler of enterprise AI strategy. 'This survey highlights a pivotal shift in retail: AI is moving decisively from experimentation to scaled execution. Retailers are leveraging AI to deliver more adaptive, personalized customer experiences powered by high-quality, unified customer data,' said Tapan Patel, research director at IDC. 'Retailers who integrate AI into core workflows—across supply chain, merchandising, and engagement—are setting the new standards for customer experience in an increasingly dynamic market.' Data Gaps and Technical Barriers Persist Despite high levels of optimism, the report reveals several key barriers: 58% of respondents say their customer data is fragmented or incomplete 46% cite high costs of AI tools as a top challenge 35% note limited technical expertise Only 21% are 'very confident' in their ability to understand and act on customer data. Amperity helps retailers close the gap between AI ambition and execution. By unifying fragmented customer data, resolving identities with precision, and making insights accessible across the business, Amperity gives retailers the AI-ready foundation they need to move faster and compete smarter. Built for enterprise scale and privacy-conscious activation, Amperity's Customer Data Cloud turns data into a growth engine—powering personalized experiences, smarter decisions, and measurable ROI. Get the full 2025 State of AI in Retail report to learn how leading retailers are using customer data to close the gap between AI potential and business results. About Amperity Amperity's Customer Data Cloud empowers brands to transform raw customer data into strategic business assets with unprecedented speed and accuracy. Through AI-powered identity resolution, customizable data models, and intelligent automation, Amperity helps technologists eliminate data bottlenecks and accelerate business impact. More than 400 leading brands worldwide, including Virgin Atlantic, Dr Martens, Wyndham Hotels & Resorts and Reckitt rely on Amperity to drive customer insights and revenue growth. Founded in 2016, Amperity operates globally with offices in Seattle, New York City, London, and Melbourne. For more information, visit or follow us on LinkedIn, X, Facebook and Instagram.
Forbes
2 days ago
- Forbes
Cloud Cost Optimization Starts With Executive Ownership
Andres Zunino, cofounder of ZirconTech. An AWS partner delivering optimized and secure cloud, web and blockchain solutions. Cloud spending is still rising faster than revenue for many companies, and leadership can no longer claim that the bill is a technical mystery. The 2025 State of the Cloud survey shows that 84% of organizations now place cost control at the top of their agenda, even though average spend already runs 17% above budget. Analysts at IDC calculate that roughly a quarter of public-cloud dollars buy no real value, confirming that software tools alone cannot close the gap between what companies pay and the benefits they receive. Rethinking Cost Reviews As Strategic Discipline Many executives still schedule cost reviews as back-office chores that surface long after engineers have launched new workloads. That habit quietly funds waste instead of innovation. True optimization begins when senior leaders treat every cloud dollar as capital that must earn a return, demand clear attribution between spend and the customers or products that drive it, and weave cost awareness into day-to-day engineering practice rather than relying on frantic year-end audits. Speed Hides Waste Speed is the cloud's main attraction, yet the same velocity often hides waste. Development teams spin up new regions, serverless functions and artificial-intelligence services whenever opportunity appears. The AWS Well-Architected Cost Optimization Pillar warns that idle resources and oversized capacity remain the largest culprits, even in mature environments. Visibility degrades just as quickly. According to the 2024 State of Cloud Cost Intelligence report, only 30% of companies can trace even half of their bill to the workloads that produced it. Finance teams that lack line-of-sight data must resort to blunt budget cuts, which sap morale and often miss the true sources of waste. Culture, Not Gadgets, Drive Visibility Culture, not gadgets, fixes that blind spot. Fewer than 15% of organizations operate policy and governance at full-run maturity, meaning most still rely on sporadic manual reviews, notes the FinOps Foundation. Someone in the C-suite—typically the chief financial officer or chief technology officer—must own cloud economics end to end, so product, finance and engineering can settle trade-offs in real time instead of escalating every decision. Clear ownership also makes it possible to reward teams for improving unit cost, not just for releasing features. Codify Cost Controls Into Delivery Pipelines Codified policy turns good intentions into measurable savings. Embedding FinOps rules directly in CI/CD pipelines can block non-compliant resources before they reach production—a practice that could free nearly $120 billion each year if adopted broadly, according to a McKinsey analysis. Governance written as code behaves like an automated unit test developers cannot bypass, keeping new launches within budget while preserving delivery speed. Evolving Governance With The Platform Governance must evolve as fast as the cloud platform. Microsoft's Azure Cloud Adoption Framework advises teams to review cost policies whenever new services, regions or pricing models appear. On Amazon Web Services, reference implementations show how AWS Config conformance packs can scan hundreds of accounts for mis-tagged or oversized assets and remediate violations automatically. Automation turns best-practice slide decks into enforceable reality, giving engineering rapid feedback while providing finance the transparency it needs. Turning Waste Into Strategic Capital The financial upside is enormous. IDC forecasts that global public-cloud spending will reach $1.35 trillion in 2027. Shaving a single percentage point off unit cost would redirect more than $10 billion each year toward faster feature delivery, new geographic launches, or richer customer experiences. Firms that track spend with the same rigor they apply to reliability and security compound those gains month after month and create a durable advantage. Cloud computing remains a potent lever for growth, yet its flexibility becomes a liability when financial discipline lags behind engineering momentum. Leaders who assign clear ownership, insist on outcome-based cost attribution and weave automated guardrails into the delivery pipeline will convert wasted spend into strategic capital. In a market racing toward trillion-dollar scale, disciplined FinOps is not housekeeping—it is the edge that separates companies that merely pay for the cloud from those that profit from it. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Yahoo
2 days ago
- Yahoo
Is C3.ai the Enterprise AI Stock to Watch?
Key Points The opportunity in enterprise AI is huge. has the ingredients to build a sustainable enterprise AI business. There are risks that could derail expansion. 10 stocks we like better than › Artificial intelligence (AI) is transforming the way companies operate. But while much of the spotlight has been on consumer applications like ChatGPT, a quieter -- and potentially more lucrative -- revolution is unfolding behind the scenes: enterprise AI. (NYSE: AI) is one of the few publicly traded companies positioned squarely in this space. It offers a specialized platform to help large organizations build, deploy, and scale AI applications tailored to their business needs. With big-name customers and a first-mover advantage, the company has captured the attention of investors. But is it the best way to play the enterprise AI boom? Let's break it down. What is enterprise AI -- and why it matters Enterprise AI refers to the application of artificial intelligence in business operations, encompassing functions such as supply chain management, customer service, cybersecurity, fraud detection, and other related areas. Unlike consumer AI, which targets individual users, enterprise AI helps companies automate processes, make data-driven decisions, and boost productivity at scale. The enterprise AI is no small market. According to a study by International Data Corp., global enterprise AI spending is expected to reach $423 billion by 2027, driven by demand across various sectors, including manufacturing, energy, healthcare, and finance. McKinsey estimates that AI could generate up to $4.4 trillion in added productivity growth, with enterprise use cases accounting for a significant portion of that. In short, this is a massive and rapidly growing space, and we're still in the early stages. How fits into the picture Founded in 2009 by Thomas Siebel, core purpose has always been to deliver AI solutions to enterprises. Its value proposition lies in its three major platforms -- C3 Agentic AI Platform, C3 AI Applications, and C3 Generative AI. The C3 Agentic AI Platform is a development suite that enables organizations to build, deploy, and manage large-scale AI applications rapidly. Enterprises can also rely on C3 AI Applications -- prebuilt, industry-specific solutions -- for industries such as energy, manufacturing, aerospace, and defense, to accelerate their AI transformations further. What sets apart is its focus on heavy, regulated industries, such as defense, oil and gas, utilities, and manufacturing, partnering with major companies like Baker Hughes and Shell to build industry-specific AI solutions. Unlike newcomers who have little domain knowledge, AI tools are built with a specific purpose, catering to the complex operational needs of large enterprises in these sectors. With deep domain understanding, it is positioned to leverage any new AI technology and scale faster in the future. For instance, it introduced its third platform, C3 Generative AI, a library of domain-specific, agentic AI applications that allow employees to interact with enterprise systems. These solutions position the company for expansion in the years to come, even after it delivered its record year in fiscal 2025 (year ended March 31, 2025), when revenue rose 25% to $389.1 million. In other words, it's not just chasing the hype like many AI companies; it's building the infrastructure for enterprise AI! What risks should investors watch? Despite its strategic positioning, riding the massive AI tailwind, faces two significant risks: cash burn and competition. The company remains unprofitable. In fiscal 2025, it posted a net loss of $289 million. Although it has a solid cash balance of over $700 million, sustained losses could still pose a significant problem as it doubles down on investments to grow market share. The silver lining is that revenue is ramping up quickly, so if the AI company can maintain a lean cost structure, it stands a good chance of reducing its losses and achieving a break-even point. Still, this could be a few years down the road. Then there's competition. Enterprise AI is heating up fast. Cloud giants like Microsoft (via Azure and OpenAI), Amazon (via Bedrock), and Oracle are embedding AI into their platforms. Many existing customers may eventually prefer bundling AI solutions directly through their cloud providers -- a significant risk to long-term expansion. And let's not forget the elephant in the room for enterprise AI, Palantir Technologies, which will forever be a head-on competitor for Fortunately, the AI market is vast and growing, providing sufficient room for multiple players to succeed. Still, investors should track how performs compared to its peers in the coming quarters. What does it mean for investors? is a high-risk, high-reward play on enterprise AI. Its platform and early customer base provide a solid foundation. If management executes well, could become a key enabler of the AI transformation happening across global enterprises. The downside is that the path to profitability remains uncertain, and competition is intensifying rapidly. For investors bullish on the enterprise AI trend, is one of the most direct public vehicles available. Be prepared for volatility, though, and keep a close eye on the company's performance moving forward. Should you buy stock in right now? Before you buy stock in consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $636,628!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,063,471!* Now, it's worth noting Stock Advisor's total average return is 1,041% — a market-crushing outperformance compared to 183% for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of July 28, 2025 Lawrence Nga has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Amazon, Microsoft, Oracle, and Palantir Technologies. The Motley Fool recommends and recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy. Is the Enterprise AI Stock to Watch? was originally published by The Motley Fool Sign in to access your portfolio
