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Our advisory services are designed to help you plan, secure, and scale PostgreSQL deployments with speed and clarity. Expert-led, practical advice across upgrades, migrations, cloud, security, and AI. Fast, streamlined engagement and delivery models to simplify approvals. Future-ready support to align PostgreSQL with your business, compliance, and innovation goals.

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OEE is one of the most powerful metrics in manufacturing, but only if you can act on it. FreshBI takes your raw OEE data and transforms it into real-time recommendations that show exactly where your biggest losses come from and the fastest way to fix them. If your team is working hard but still struggling with downtime, slow cycles, or inconsistent output, this dashboard will give you the clarity you’ve been missing. Schedule a call and let’s walk you through the platform.

Most OEE dashboards only show you what happened. FreshBI shows you what will happen next and how to prevent losses before they impact production. With AI recommendations at every stage, your team knows when and where equipment efficiency is falling, and the exact levers to pull to reverse it. If you’re ready to turn OEE into a competitive advantage, book a call with FreshBI and get a walkthrough of the platform.

High-performance analytics shouldn't come with high-anxiety pricing. 📉 Firebolt’s decoupled storage and compute architecture delivers total multidimensional elasticity—meaning you only pay for what you use, not for idle capacity. Achieve up to 80% better price-performance than legacy warehouses and keep your data budget as predictable as your growth.

Another year, another list of ambitious goals. What if you could cross the first ones off before January even ends?

Your dev team should be perfecting your core product, not reinventing the pivot table wheel. Join the market leaders who choose to embed, not build. Flexmonster delivers enterprise-grade reporting that integrates in minutes: ✅ Handles massive datasets with ease ✅ Lightning-fast data visualization ✅ Native-fit UI Try the Live Demo!

Cut development time by embedding Flexmonster directly into your app. It’s a full-featured pivot table component designed to look and feel like a native part of your software. ✔️Native feel: Looks and performs exactly like your own app/solution/ ✔️Framework-ready: React, Angular, Vue, and beyond. ✔️Feature-rich: Sorting, filtering, and grouping out of the box. Focus on your core product. Rely on Flexmonster to handle the data visualization.

AI agents are moving from answering questions to taking action. They are approving workflows. Triggering payments. Updating records. Responding to customers. Making operational decisions. But there is one question enterprises need to answer before scaling agentic AI: What happens when a good AI agent acts on bad data? Most AI observability tools can help teams understand what went wrong after the fact. But if an agent has already processed the payment, approved the claim, updated inventory, or sent the customer response, the damage may already be done. That is the problem we are working on at FirstEigen. We are preparing to introduce AgentBuck, a new product built for the agentic AI era. AgentBuck is designed to help enterprises discover which AI agents are running, understand what data those agents depend on, continuously validate that data, and prevent risky records from reaching the agent before action happens. In simple terms: AgentBuck is being built to make bad data invisible to AI agents. If a record is incomplete, abnormal, non-compliant, duplicated, stale, or contextually unfit for purpose, the goal is to quarantine it before the agent acts on it. Because AI agents do not just need better models. They need trusted data. And in autonomous workflows, trust cannot wait for an alert. It has to be enforced at runtime. More coming soon. AI agents are only as safe as the data they act on. #AgenticAI #EnterpriseAI #DataQuality #AITrust #DataGovernance #DataObservability #FirstEigen #AgentBuck #DataBuck

Is your data ready for AI agents? Ask these 5 questions first. Before scaling AI across the business, leaders should pressure-test the data foundation behind it. 1. Can we trace the answer? When an AI agent gives a business-critical output, can we explain where that answer came from? 2. Can we catch changes early? If business logic, rules, or data patterns shift, will we know before users are affected? 3. Can we prove the data was trusted at the time of use? Not just clean in general, but reliable for that specific decision, report, or AI workflow. 4. Is someone accountable when quality drops? Do we know who owns the fix, how fast it should happen, and what action to take? 5. Can business teams see the confidence level? Trust in AI should not live only with engineering. Business users need clear visibility too. If too many answers are “not yet,” the problem is not AI ambition. It is data readiness. And that is useful news because it shows exactly where to strengthen the foundation before scaling AI further. 💭 How many of the five would your current data stack pass today? Reply with your score out of 5. #AIReadiness #AIAgents #DataTrust #EnterpriseAI #DataQuality

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Which of your training sources would fail an audit today? Most teams can't answer. The cost lands later: a model that quietly underperforms in exactly the segments the bad source covered. We verify every source before it ships. Provenance tagged, field by field. Get a source-quality audit.

We'll be the first to say it: if you need one source scraped once, don't call us. But if you need many sources, refreshed on a cadence, delivered to a custom schema, and your best engineers free to build the actual product: · Your team stays on the model, not the pipeline · Acquisition runs on whatever cadence the product needs · One partner owns the whole stack, nothing to reconcile We acquire the data. You build the AI. Get in touch.

Generic databases bury the signal. FounderNest surfaces the right biotechs, patents and clinical trials in seconds and not weeks. Here's how key pharma and healthcare companies are doing market intelligence the efficient way.

85% of pharma and biotech acquisition teams say they've missed a strategic partnership because they found it too late. This is what finding it first looks like.

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When I speak with leaders in food delivery, one theme always comes up: decisions are being made with incomplete or biased data. London is one of the most competitive food delivery markets in the world. Yet until now, no reliable benchmark was available to the industry. Reports like these are usually locked behind paywalls or kept for internal use only. At DoubleData, we specialise in the food delivery sector. Our team scrapes and matches millions of data points every month with 99.9% accuracy, helping executives make faster and smarter decisions. That is why we created the Food Delivery Benchmark Report: Uber Eats in London (2025) and made it freely available. Based on 691 restaurants across three key zones (E1, SE1, CR0), it reveals: ✅ Why quality, not quantity, drives customer loyalty ✅ Where London’s biggest “quality deserts” are hiding ✅ How promotions and logistics shape competitive advantage 👉 Download the report here: https://lnkd.in/ged8cnKd This is the first open benchmark of its kind in food delivery. And it will not stop with London. We are building benchmarks for major markets around the world because reliable, high-quality data should not be a privilege reserved for a few. Over the next weeks, I will share the most eye-opening insights from London right here. Stay tuned.

Across the UK, intense competition is forcing platforms into a promotional race-to-the-bottom. But are endless percentage discounts what customers really want? Our 2025 benchmark, analysing promotions on the Uber Eats platform in London, suggests the market is being misread. The battle for the customer is being won on creative value, not just on price. The data from Uber Eats reveals: ✅ Across all key London zones, the most dominant promotional strategies are not classic discounts. ✅ Instead, ‘Value-Added Promos’ (e.g., 'Buy 1, Get 1 Free', free items) and other complex, value-driven offers are the tactics that truly resonate with customers. This is a critical insight for any marketing leader. It proves you can compete more intelligently without simply destroying your margins. The strategic question must shift from "what discount can we offer?" to "what unique value can we provide?". Your platform tools and partner conversations must reflect this reality. We break down the complete 'Promotional DNA' of Uber Eats in London in our free report. 👉 Download the 2025 Food Delivery Benchmark here: https://lnkd.in/ged8cnKd

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Got the Btrieve blues? Switch to FairCom ISAM. Use all the API calls you’re used to, along with SQL, JSON, and more.

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