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Salesforce Tightens Slack’s API Rules
16Jun

Salesforce Tightens Slack’s API Rules

Salesforce Tightens Slack’s API Rules, Restricting AI Data Access Salesforce, the parent company of workplace messaging platform Slack, has quietly updated its API terms to block third-party software firms from indexing or storing Slack messages—a move that could significantly impact enterprise AI tools. According to a report from The Information, the changes prevent apps like Glean (a workplace AI search provider) from accessing Slack data for long-term storage or analysis. In a statement to Reuters, Salesforce framed the shift as a data security measure, saying: “As AI raises critical considerations around how customer data is handled, we’re reinforcing safeguards around how data accessed via Slack APIs can be stored, used, and shared.” What Does This Actually Mean? APIs (Application Programming Interfaces) allow different software systems to communicate. Until now, companies could use Slack’s API to: Now, those capabilities are restricted. Third-party apps can still access Slack data in real time, but they can’t retain it—meaning AI models can’t learn from past conversations. Glean reportedly warned customers that the change “hampers your ability to use your data with your chosen enterprise AI platform.” Why Is Salesforce Doing This? Officially, the company says it’s about security and responsible AI. But critics argue it’s a strategic lock-in play: Industry Backlash: “This Is Anti-Innovation” The move has sparked frustration across the tech sector, with critics accusing Salesforce of building a walled garden: The Bigger Picture: AI’s Data Wars This isn’t just about Slack—it’s part of a broader battle over AI training data: Salesforce’s move suggests that enterprise AI will increasingly run on proprietary data silos—meaning companies that control the data control the AI. What Happens Next? One thing’s clear: The age of open data for AI is ending—and the age of data feudalism is here. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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June 16, 2025in AI Tools, Data, Enterprise, Google, Laws, Salesforce, Salesforce Slack
Marketing Cloud Intelligence
26May

5 Ways Marketing Intelligence Transforms Campaign Performance and ROI

Struggling to prove marketing ROI? You’re not alone. Are you optimizing campaigns in real time—or just reacting to yesterday’s results? Can you confidently tie marketing spend to revenue, or are you relying on guesswork? If fragmented data, delayed insights, and wasted ad spend are holding you back, Salesforce Marketing Intelligence is the solution. This AI-powered analytics platform unifies your marketing data, automates optimizations, and delivers actionable insights—so you can boost performance, reduce waste, and maximize ROI. The Challenge: Turning Data into Revenue Today’s customer journey spans social, email, search, and more—but without clear insights, optimizing spend and proving impact is nearly impossible. Traditional analytics leave marketers with: Marketing Intelligence changes that. What Is Marketing Intelligence? Salesforce Marketing Intelligence is an AI-driven analytics solution that:✅ Unifies marketing data in real time✅ Automates optimizations with AI agents✅ Delivers actionable insights to improve ROI Built on Data Cloud, Tableau, and Einstein AI, it transforms raw data into smart, autonomous decisions—so you spend less time analyzing and more time executing high-impact strategies. 5 Breakthrough Innovations in Marketing Intelligence 1. AI-Powered Paid Media Optimization Autonomous agents analyze performance data 24/7, automatically: 2. Real-Time Performance Dashboard (Marketer Homepage) Get an instant, AI-summarized view of all campaigns—with alerts for underperforming ads and one-click optimizations. 3. AI Data Enrichment & Cleaning No more messy spreadsheets. AI standardizes and categorizes your data (e.g., grouping “Meta” and “Reddit” as “Social Channels”) for clearer insights. 4. 3-Click Data Integration Connect Google Ads, Meta, Shopify, CRM, and more in seconds with pre-built connectors—no coding needed. 5. End-to-End Attribution Tracking See the full customer journey—from first click to closed deal—with built-in first- and last-touch attribution. Marketing Intelligence in Action: A Retailer’s Success Story Your Garden Place (YGP), a sustainable home goods brand, used Marketing Intelligence to: Result: Higher conversions, lower wasted spend, and data-backed confidence in every decision. Stop Guessing. Start Optimizing. Marketing Intelligence eliminates the guesswork—giving you real-time insights, AI-driven optimizations, and closed-loop attribution—all on the Salesforce platform. Ready to transform your marketing performance? Reach out to Tectonic to explore Marketing Intelligence today. “A top priority for marketers is understanding performance in real time. Marketing Intelligence provides instant insights and autonomous actions—ensuring every dollar drives impact.”—Stephen Hammond, GM, Marketing Cloud Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 26, 2025in Data, Google, Marketing Intelligence, Salesforce
ai agents
29Mar

AI Agents

What AI Agents Are Available on the Market? Limitations of Operator, Computer Use, and Similar Agents OpenAI Operator can be seen as a semi-autonomous agent, but many users note that it asks too many questions and requires excessive confirmations, even in situations that pose no risk:“Operator is like driving a car with cruise control — occasionally taking your foot off the pedals — but it’s far from full-blown autopilot.” Furthermore, although Operator is technically designed to interact with any website, in reality, it’s far from a universal solution. It works reliably on a predefined set of platforms for tasks like shopping and restaurant reservations (such as Instacart and OpenTable), where its functionality has been tested. But outside of these, its performance is inconsistent — sometimes even generating incorrect or entirely fabricated data. Google’s Project Mariner, which aims to offer similar capabilities within Chrome, remains in closed beta for now. Meanwhile, many are eagerly anticipating a consumer product from Claude, which released the API for its Claude Computer Use agent (built on a slightly different principles) back in October 2024. One thing seems certain, though — it will be even more “cautious” than Operator, meaning it’s unlikely to handle tasks like sending emails or posting on social media on your behalf. Thus, browser-based agents come with at least two key limitations:— they work reliably only on a predefined set of websites;— certain actions are prohibited (for example, allowing an agent to send emails autonomously could create conflicts between its owner and others). Mobile agents face similar constraints. Take Perplexity Assistant, one of the earliest attempts at a “versatile” mobile AI agent — it still supports only a limited range of apps where it can operate on behalf of the user. Deep Research Agents To highlight the contrast, let’s look at AI agents built specifically for deep research. This category has seen a surge in new tools recently, and they deliver significantly better results than standard AI-powered web search. Deep Research tools qualify as AI agents due to their high level of autonomy. At this stage, no truly agentic tool exists that can handle any problem on our behalf — even in a semi-autonomous mode, let alone a fully autonomous one. However, there are highly effective agents within specific domains, such as deep research agents. With that in mind, let’s categorize typical AI applications into several groups (use cases) and tackle the following question for each group. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 29, 2025in Data, Google, Salesforce
unpatched ai
05Feb

Unpatched.ai

The Mystery of Unpatched.ai: AI-Powered Vulnerability Discovery Raises Questions During January’s Patch Tuesday, Microsoft credited Unpatched.ai for reporting multiple high-severity vulnerabilities. Yet, despite its contributions, the AI-driven bug-finding tool remains an enigma to the cybersecurity community. Last month, Microsoft addressed 159 new vulnerabilities across its widely used products. Among them, Unpatched.ai was acknowledged for identifying three remote code execution flaws—CVE-2025-21186, CVE-2025-21366, and CVE-2025-21395—all of which affect Microsoft Access and received a CVSS score of 7.8. While Microsoft’s recognition highlights Unpatched.ai’s role in vulnerability discovery, little is known about the tool itself. Informa TechTarget reached out to multiple security vendors and experts for insights, but responses only deepened the mystery. A Cryptic Online Presence Unpatched.ai describes itself as “vulnerability discovery by an AI-guided cybersecurity platform” on its website. It provides a list of reported vulnerabilities, which consists solely of Microsoft-related flaws—primarily within Microsoft Access. The platform states that it collaborates with “select enterprise, government, and security vendors based in the U.S. and ally countries.” The company’s “About” page sheds some light on its mission, attributing its research to the need for greater transparency around unpatched software flaws: “We find unpatched issues in software to help customers better identify and manage cyber risk. Many issues are unknown or silently fixed by software vendors, hiding the true risk profile of their products. With the help of AI, we are developing an automated platform to help find and analyze these issues for our customers.” Beyond the website, Unpatched.ai maintains an X account, though much of its activity has been erased. A now-deleted post from January 29 warned that Microsoft’s patch for CVE-2025-21396 was insufficient. When contacted about the post, a Microsoft spokesperson responded, “We are aware of these reports and will take action as needed to help protect customers.” However, Microsoft did not provide additional background on Unpatched.ai. Attempts to reach Unpatched.ai directly have gone unanswered. Piecing Together the Puzzle Efforts to uncover more about Unpatched.ai yielded few concrete details. The domain was registered through Namecheap in September, with ownership masked by a privacy service based in Reykjavik, Iceland. Adam Barnett, lead software engineer at Rapid7, noted that beyond Unpatched.ai’s website, information is scarce. However, he identified a Reddit user, “Fit_Tie_9430,” who has claimed affiliation with the platform. This user shared details about Unpatched.ai’s vulnerability discoveries and linked to now-private YouTube videos demonstrating exploits against Microsoft Access vulnerabilities. Barnett pointed out that Unpatched.ai was also credited for a December Patch Tuesday flaw, CVE-2024-49142. Initially published without attribution, Microsoft later updated the advisory to acknowledge Unpatched.ai’s discovery. Interestingly, the Unpatched.ai website’s favicon—a simple “:)” emoticon—appears to reference the Windows Blue Screen of Death’s “:(” symbol. “It’s a nice touch,” Barnett said, “but I still don’t know who’s behind it. It could be just about anyone with the time, resources, and skills.” Other industry experts share the same uncertainty. Satnam Narang, senior staff research engineer at Tenable, observed that Unpatched.ai’s X account follows only a handful of infosec professionals. “It’s unclear if the service is still in a closed-door phase and will eventually provide more insights about its leadership and team, or who may be backing it,” he said. Alon Yamin, co-founder and CEO of Copyleaks, noted that an AI-driven vulnerability discovery platform was inevitable given the surge in software flaws. While AI can be a game-changer for proactive threat detection, he cautioned against potential misuse. “It’s crucial that Unpatched.ai is deployed carefully, responsibly, and ethically, with safeguards to prevent attackers from exploiting the vulnerabilities it identifies,” Yamin said. The Future of AI-Powered Bug Hunting AI-driven vulnerability discovery is an emerging focus in cybersecurity, though few major breakthroughs have been publicly confirmed. In November, Google announced it had discovered a zero-day vulnerability using AI. Google Project Zero and DeepMind’s AI-powered agent, Big Sleep, identified a buffer stack underflow flaw in the SQLite open-source database engine. With Unpatched.ai making waves yet remaining elusive, the cybersecurity community is left with more questions than answers. Is this the beginning of a new era in AI-powered vulnerability research, or is Unpatched.ai an outlier? Until more information surfaces, the mystery remains. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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February 5, 2025in Data, Enterprise, Google, Laws
healthcare Can prioritize ai governance
07Nov

AI Data Privacy and Security

Three Key Generative AI Data Privacy and Security Concerns The rise of generative AI is reshaping the digital landscape, introducing powerful tools like ChatGPT and Microsoft Copilot into the hands of professionals, students, and casual users alike. From creating AI-generated art to summarizing complex texts, generative AI (GenAI) is transforming workflows and sparking innovation. However, for information security and privacy professionals, this rapid proliferation also brings significant challenges in data governance and protection. Below are three critical data privacy and security concerns tied to generative AI: 1. Who Owns the Data? Data ownership is a contentious issue in the age of generative AI. In the European Union, the General Data Protection Regulation (GDPR) asserts that individuals own their personal data. In contrast, data ownership laws in the United States are less clear-cut, with recent state-level regulations echoing GDPR’s principles but failing to resolve ambiguity. Generative AI often ingests vast amounts of data, much of which may not belong to the person uploading it. This creates legal risks for both users and AI model providers, especially when third-party data is involved. Cases surrounding intellectual property, such as controversies involving Slack, Reddit, and LinkedIn, highlight public resistance to having personal data used for AI training. As lawsuits in this arena emerge, prior intellectual property rulings could shape the legal landscape for generative AI. 2. What Data Can Be Derived from LLM Output? Generative AI models are designed to be helpful, but they can inadvertently expose sensitive or proprietary information submitted during training. This risk has made many wary of uploading critical data into AI models. Techniques like tokenization, anonymization, and pseudonymization can reduce these risks by obscuring sensitive data before it is fed into AI systems. However, these practices may compromise the model’s performance by limiting the quality and specificity of the training data. Advocates for GenAI stress that high-quality, accurate data is essential to achieving the best results, which adds to the complexity of balancing privacy with performance. 3. Can the Output Be Trusted? The phenomenon of “hallucinations” — when generative AI produces incorrect or fabricated information — poses another significant concern. Whether these errors stem from poor training, flawed data, or malicious intent, they raise questions about the reliability of GenAI outputs. The impact of hallucinations varies depending on the context. While some errors may cause minor inconveniences, others could have serious or even dangerous consequences, particularly in sensitive domains like healthcare or legal advisory. As generative AI continues to evolve, ensuring the accuracy and integrity of its outputs will remain a top priority. The Generative AI Data Governance Imperative Generative AI’s transformative power lies in its ability to leverage vast amounts of information. For information security, data privacy, and governance professionals, this means grappling with key questions, such as: With high stakes and no way to reverse intellectual property violations, the need for robust data governance frameworks is urgent. As society navigates this transformative era, balancing innovation with responsibility will determine whether generative AI becomes a tool for progress or a source of new challenges. While generative AI heralds a bold future, history reminds us that groundbreaking advancements often come with growing pains. It is the responsibility of stakeholders to anticipate and address these challenges to ensure a safer and more equitable AI-powered world. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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November 7, 2024in Data, Generative AI, Laws
Reddit Acquires Memorable AI
08May

Reddit Acquires Memorable AI

Reddit Acquires Memorable AI to Enhance Ad Campaign Performance Reddit has acquired Memorable AI, an ad creative optimization platform, in a strategic move to enhance ad campaign performance and impact for its advertisers. This acquisition will integrate Memorable AI’s advanced tools into Reddit’s ad stack, offering benefits such as creative insights, improved effectiveness, and automation to maximize ad performance and return on ad spend. “Memorable AI has a proven ability to optimize ad creative for the best possible results before an ad even runs,” said Reddit Chief Operating Officer Jen Wong. “By incorporating Memorable AI’s capabilities, Reddit will advance its efforts in optimizing, generating, and selecting ad creatives to deliver superior results for our advertisers. We are excited to welcome the Memorable AI team to Reddit.” Recently recognized as one of Gartner’s Cool Vendors in Generative AI for Marketing 2024, Memorable AI specializes in estimating the impact of ad creatives across metrics like click-through, engagement, view-through rates, brand lift, and conversion rates. This acquisition follows Reddit’s recent purchase of audience contextualization company Spiketrap. Reddit Acquires Memorable AI Sebastian Acevedo, Co-Founder of Memorable AI, commented, “Over the past three years, we have focused on developing cutting-edge creative intelligence products. Our state-of-the-art machine learning models help top global advertisers analyze their creatives, predict their impact, and achieve double-digit improvements with actionable insights. We are thrilled to elevate this technology with Reddit’s extensive customer base. This acquisition positions Reddit as a leader in creative effectiveness AI, and its advertisers will greatly benefit from AI-driven creative pretests and recommendations.” The Memorable AI team has joined Reddit and will lead projects across Reddit’s ads business, driving forward innovative solutions for ad performance. Like Related Posts Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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May 8, 2024in Generative AI
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