Solix Technologies, Inc.

As Vice President at Solix Technologies, I lead strategic initiatives that drive the company’s mission to provide innovative data management solutions. With a focus on enabling enterprises to unlock the value of their data, I oversee a dynamic team that develops and implements cutting-edge solutions in areas such as data archiving, data governance, and compliance. 

A key area of focus is our Solix Enterprise AI product, which leverages advanced machine learning and AI-driven analytics to help organizations optimize their data workflows and improve operational efficiency. By enabling smarter, data-driven decisions, Enterprise AI empowers businesses to unlock deeper insights, streamline processes, and drive innovation. 

My role involves working closely with cross-functional teams to foster business growth, enhance customer satisfaction, and ensure operational excellence while positioning Solix as the leader in the data management industry.

VP of Sales

Solix Technologies is a leading provider of comprehensive data management solutions, empowering enterprises to efficiently manage, protect, and unlock the full value of their data. With a focus on innovation and scalability, Solix offers a suite of powerful products designed to address the evolving needs of modern organizations. 

Our Enterprise AI product harnesses the power of machine learning and advanced analytics to optimize data workflows, improve decision-making, and drive operational efficiency. The Enterprise Archiving solution helps businesses manage massive volumes of data while ensuring compliance, cost savings, and seamless retrieval. Additionally, our Data Lake product enables organizations to store, integrate, and analyze vast amounts of structured and unstructured data, supporting advanced analytics and AI-driven insights. 

Proven over two decades in the industry, Solix is a leader in Enterprise Data Management and AI, helping organizations transform their data into a strategic asset for growth and innovation.

Sr Enterprise Sales Director

SION

SION is a leader in the technology/software industry for international logistics. Our software demonstrates that the future of logistics is in business analytics technology. SION's state-of-the-art software is easy to use, flexible, and highly scalable, adapting to a supply chain’s changing management needs. With SION companies can stay in tune with technological advancements through its agile end-to-end digital thread.

Assisting clients to make better decisions with dynamic real-time analysis, leveraging the latest technology by in-house data scientists. SION is especially beneficial for multinational businesses with its real-time supply and demand monitoring, delivery tracking, and more. is integrated into every corner of your business and enables you to make better decisions, achieve end-to-end visibility, and deliver best-in-class customer experiences. SION provides unparalleled reporting visibility, giving SCM a full picture of its total business and logistics with SION.

Oracle

Oracle Cloud is the first public cloud built from the ground up to be a better cloud for every application. By rethinking core engineering and systems design for cloud computing, Oracle created innovations that accelerate migrations, deliver better reliability and performance for all applications, and offer the complete services customers need to build innovative cloud applications.

OCI’s Cloud Adoption Framework helps organizations facilitate their transition to the cloud by offering a valuable collection of cloud resources, best practices, tutorials, and enablement tools. This framework helps customers define a robust cloud strategy, plan for successful workload migration, and ensure complete manageability of cloud environments. The Cloud Adoption Framework provides customers with a methodology to use Oracle Cloud built-in efficiencies such as Cloud Lift Services, and key-value programs, including Oracle Support Rewards.

https://www.oracle.com/cloud/

Enterprise Sales Director | Oracle Cloud

PERSTRADA

Perstrada specializes in the invention and development of specialty nutraceutical and pharmaceutical products and novel formulation technologies.
We provide formulation, analytical, and manufacturing services to nutraceutical and pharmaceutical companies, working collaboratively to provide innovative solutions to challenging drug delivery problems and to create advanced medicines.
FORMULATION:
Perstrada’s expertise involves finding the most effective method of drug delivery for poorly water-soluble molecules.  Our comprehensive range of capabilities enables clients to optimize their drug product formulation prior to initiating expensive clinical development. 
LIFE-CYCLE MANAGEMENT AND 505(b)(2) PRODUCT DEVELOPMENT:
Perstrada is dedicated to the solubility and bioavailability enhancement of difficult-to-formulate compounds.  Our proprietary product development programs focus on creating novel specialty pharmaceutical products that are improved versions of existing medicines.  
MANUFACTURE OF cGMP CLINICAL TRIAL MATERIALS:
Following formulation selection and optimization, Perstrada can transition a development program quickly to cGMP manufacture of first-in-man clinical materials.  Perstrada’s manufacturing capabilities include dosage forms for oral, topical, or parenteral administration.

Rainmaker

As an Enterprise Sales Executive specializing in B2B, my primary role was to drive new business acquisition and revenue growth by identifying and engaging high-value enterprise prospects. A focus on understanding the specific challenges and goals of each client, working closely with them to craft customized software solutions that align with their business objectives. Building strong, consultative relationships with C-level executives, IT leaders, and key stakeholders, guiding them through the sales process with a clear focus on value proposition, ROI, and scalability. 

Leading the entire sales cycle, from prospecting and lead qualification to product demonstrations, negotiations, and closing multi-million-dollar deals. Balancing both strategic planning and tactical execution, my role was to consistently meet or surpass sales targets while delivering tailored solutions that drive long-term customer success and business transformation.

National Account Director

Bradford Technologies

For over 33 years, Bradford Technologies has been dedicated to producing innovative solutions for Valuation Professionals. Ranging from the most intuitive appraisal applications available to cutting-edge Computer-Aided Appraisal Software, Bradford continues to develop trailblazing products that set the benchmark for the industry.

Since 1987, Bradford Technologies has been dedicated to producing innovative solutions for Valuation Professionals. From the most intuitive appraisal applications available to cutting-edge Computer-Aided Appraising Software and statistically supported valuation reports, Bradford continues to develop trailblazing products that set the benchmark for the industry. As the market continues to evolve, Bradford Technologies is committed to providing appraisers, appraisal management companies and lenders with the tools they need to produce statistically accurate, reliable and transparent collateral valuations.

Bradford Technologies is one of the first companies to complete the EAD integration and the first to implement the new appraisal-sharing feature in UCDP. FHA has stated it will require appraisals to be submitted through EAD portal. PortalDirect allows its users to take advantage of the new appraisal-sharing functionality.

Sales Manager

A seasoned cloud data leader and entrepreneur with over 25 years of experience in enterprise strategy and business development. Developing partnerships to ensure organizations optimize their data management and leverage the power of AI, SaaS, database, and EDM solutions. A passion for innovation and transformation, and enjoy solving complex IT challenges with cutting-edge technology.

Founder and CEO of SION and PERSTRADA, two successful companies that offer cutting-edge software for international supply chain analytics and the pharmaceutical industry. Each business achieved growth from conception to 2X annually through strategic partnerships and industry-leading technology. Specializing in establishing long-term relationships with clients and partners across various verticals.

David Zuccolotto

𝐀𝐈 𝐢𝐧 𝐃𝐫𝐮𝐠 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 𝐉𝐮𝐬𝐭 𝐇𝐢𝐭 𝐚 𝐍𝐞𝐰 𝐌𝐢𝐥𝐞𝐬𝐭𝐨𝐧𝐞

Here’s the kind of AI development that makes you think big. A major pharmaceutical firm (Merck) is teaming up with an AI-powered biotech (Valo) to look for new treatments in Parkinson’s, and the deal is worth more than three billion dollars.

What really stands out is how much this depends on strong information architecture. Models can only do so much on their own. They need clean, connected, well-organized data behind them — everything from patient records to biological samples to clinical measurements. Without that foundation, the AI can’t deliver the results everyone is hoping for.

This move shows how drug discovery is shifting toward AI-driven ecosystems. Pharma, data platforms, and large-scale datasets are coming together in ways we’ve never seen before. And the strength of the underlying data architecture is what makes it all possible.

If you want the full story, check out the link:
https://lnkd.in/gYV_3T2M

About our platform:
https://lnkd.in/gM-FhirA

Open article: Solix EAI Pharma by solix.com

I came across this interesting article: “AI cut development time of antibiotic that spares gut-friendly bacteria by two years” (Chemistry World, published 5 days ago). 
Chemistry World

What leaps out to me is how far we’ve come in applying AI not just to speed things up, but to target precision in drug development — in this case, an antibiotic that avoids collateral damage to beneficial gut microbes.

From an information architecture and data-management perspective, this rings very true:

These breakthroughs are underpinned by structured, high-quality data — mapping which bacteria are “friendly”, which are harmful, how they interact.

The AI models must integrate and reason over multiple layers of data (microbial profiles, drug-target interactions, patient safety) in a cohesive architecture.

To shrink timelines by two years, you need information pipelines that are agile, traceable and well governed — the kind of modern data-infrastructure we discuss often.

Key takeaways:

Innovating with AI in life sciences is now less about “can we” and more about “how fast and how reliably”.

The reliability of AI output depends heavily on the underlying data architecture (governance, lineage, metadata) — sloppy structure means risk.

As these methods mature, the organizations that have modern, scalable information architecture will be able to iterate faster and extract value from AI more safely.

Ethical/clinical implications matter: it’s not just about speed, but ensuring the drug spares beneficial bacteria, for example — which means richer datasets, clearer definitions of harm/benefit and stronger traceability of decisions.

In short: If you treat AI as a glitzy “tool”, you miss the point. The real differentiator is how you build the end-to-end information architecture that enables that AI tool to work with reliability, speed and integrity.

Here’s the article link:

Open article: AI cut development time of antibiotic that spares gut-friendly bacteria by two years by chemistryworld.com

AI cut development time of antibiotic that spares gut-friendly bacteria by two years

AI Ethics Start at Data Architecture—An Uncomfortable Truth

Let’s be blunt: If you’re not obsessively building ethics into your Information Architecture, you’re playing with fire. People love to talk about “ethical AI” as if you sprinkle some disclaimers on your website and build a half-hearted “AI Ethics Board.” But without data-level governance, all of that is performative. Our increasingly dystopian headlines (biased hiring tools, facial recognition gone haywire, AI content that spreads misinformation) stem directly from data neglect.

Why does IA matter for ethics? Because the darkest corners of biased AI, privacy breaches, and regulatory fines start here:

Hidden Bias Lives in Messy If your data architecture doesn’t enforce diversity and fairness constraints, your AI will perpetuate historical biases. Your “cool new hiring AI” might unintentionally reject candidates from underrepresented backgrounds because those groups were undercounted in your legacy HR systems.

Unchecked Privacy Violations: Without clear data lineage and classification, you risk feeding protected information (health records, personal IDs) into models that shouldn’t see them. One slip, and you’re staring down a class-action lawsuit—not to mention collapsed trust.

Opaque Decision-Making: If you can’t trace how data travels through your pipelines—what transformations it undergoes—your AI decisions become black boxes. Regulators demand accountability, and rightly so. If you can’t explain how your AI arrived at a loan decision or a healthcare recommendation, you’re toast.

Now for the provocative part: If you think ethics is something you tack on after the fact, you’re delusional. Ethical AI begins at a data level:

Tag and classify sensitive data at ingestion. If technical teams can’t distinguish PII from anonymized info, they’ll inadvertently misuse it.

Embed bias detection in your pipelines. Identify if certain demographic groups are underrepresented or misrepresented.

Ensure audit trails for every data transformation. If you can’t prove how data got scrubbed, or who approved a schema change, you can’t prove compliance.

💡 Ethical AI isn’t a flashy checkbox; it’s baked into your data architecture. If you’re not living and breathing data governance daily, you might think you’re “ethically motivated,” but you’re one misconfig away from becoming the next cautionary headline.

𝐓𝐡𝐞 𝐃𝐚𝐭𝐚 𝐋𝐚𝐲𝐞𝐫 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐍𝐨 𝐎𝐧𝐞 𝐖𝐚𝐧𝐭𝐬 𝐭𝐨 𝐓𝐚𝐥𝐤 𝐀𝐛𝐨𝐮𝐭

I just read an article titled “Getting the enterprise data layer unstuck for AI” — and it struck me how critical the underlying data architecture really is when organizations try to scale their AI. InfoWorld

The piece argues that recent waves of AI aren’t just another tool: they’re forcing enterprises to rewrite their data layer entirely. Gone are the days when siloed tables and legacy systems could reliably support modern AI. Instead, the demand is for meaning, trust, interoperability — a foundation that truly supports intelligent systems. InfoWorld

What stands out for me:

·        Data architecture can’t be an afterthought without a data layer built for context and connectivity; AI risks being brittle or misleading.
·        The shift is not just technical — it’s philosophical. It’s about moving from “store and forget” to “store, connect, understand.”
·        Investing in clean, well-governed, interoperable data infrastructure isn’t overhead. It’s the strategic enabler for AI that delivers real value.

This push toward smarter data architecture is exactly what separates AI experiments from true enterprise-scale AI transformations. For organizations exploring AI adoption, building a resilient, future-ready data foundation should be top of mind.

Link to article: https://lnkd.in/g5AYa_Xa
More info about IA for AI: https://lnkd.in/drBppbkM

Google

Scale Fortune 500 enterprises, government agencies, and high-growth startups by architecting and deploying AI solutions that drive measurable business transformation. Deliver engagements resulting in 130%+ revenue growth, 8-figure cost savings, and AI-enabled process automation reducing operational cycle times by 81%. Lead AI adoption programs that take early-stage startups from prototype to market-leading platforms, and transform legacy enterprises into AI-driven market leaders.

Design and implement end-to-end AI ecosystems leveraging Google Vertex AI, TensorFlow Extended (TFX), and TPU v5e infrastructure. Integrate large language models (LLMs), multimodal AI pipelines, and retrieval-augmented generation (RAG) workflows tailored to domain-specific use cases. Engineer petabyte-scale data pipelines with BigQuery and Dataflow, embedding vector search for real-time semantic retrieval.

Deploy production-grade AI using GKE and Kubeflow Pipelines, enabling CI/CD-driven MLOps with automated model monitoring, drift detection, and rapid retraining. Optimize inference latency by up to 60% through TensorRT acceleration, mixed-precision computation, and graph pruning. Deliver cross-domain AI applications spanning healthcare diagnostics, real-time financial fraud detection, industrial automation, and secure defense systems, serving millions of end users worldwide.

AI Consulting Strategist – Google AI

NVIDIA

Developed GTM strategy for enterprise deployment of NVIDIA’s LLM inference stack, targeting financial services, logistics, and healthcare sectors. Led internal pilot program to monetize edge AI deployment tools for multi-modal sensor data, resulting in $60M+ in downstream enterprise contracts. Designed pricing model for inference-as-a-service API bundles; used in 4 Fortune 500 client rollouts. Partnered with engineering teams to productize low-latency LLM pipelines on A100/H100 architecture for high-frequency decision environments. Presented enterprise AI monetization playbook at NVIDIA Executive Forum; used to inform FY23 enterprise roadmap. Built economic viability framework for internal AI tooling, prioritizing initiatives with >4x projected ROI.

AI Commercialization Strategist – Enterprise Solutions

Apple

Led monetization design for Vision Pro’s AI-native features, including intent prediction, gaze tracking analytics, and adaptive content surfacing. Worked cross-functionally with ML engineers and product to translate LLM-based user modeling into paid in-app personalization APIs. Built dynamic pricing framework for AI-driven developer tools on VisionOS, projected to generate $180M+ in ARR by 2025. Defined core metrics for AI feature adoption, driving a 3.7x increase in developer conversion across beta cohorts. Presented strategic roadmap for AI revenue growth to executive leadership; approved for rollout across 4 product verticals. Contributed to Apple’s internal thesis on “Ambient AI Monetization,” later used in fiscal year investment planning

AI Monetization Strategist – Vision Pro Team

I build and monetize AI systems. At Apple, I shaped the Vision Pro AI revenue strategy. At NVIDIA, I helped commercialize LLM infrastructure for enterprise deployment. I specialize in turning ML capabilities into scalable business models, especially in environments where speed, monetization, and leverage matter more than polish. I’ve advised AI startups, contributed to strategic go-to-market plans, and built pricing frameworks now used by Fortune 500 teams. My background is technical, but my advantage is translating that into revenue. I’m open to high-leverage collaborations, especially where AI meets distribution, B2B tooling, or capital.

Rami Zwebti

Every single legendary company has three archetypes!

🔸 The visionary tyrant founder  
🔸 The stylish european designer  
🔸 The quiet geek engineer  

Apple had those ones,  
Tesla had those ones,  
Meta had those ones,  
OpenAI had those ones,  

And well, there is always the exception that proves the rule... Linux just had Linus Torvalds  

#devs #ai #software

No alternative text description for this image

AI Engineer builds a real-time potato counter using just ONE training image.

Most people assume you need huge datasets and large models to build anything useful with Al. Well, this project proves otherwise.

A senior Al engineer created a real-time potato counter for a conveyor belt using a tiny setup.
No custom dataset. No heavy model. Just one annotated frame.

He used Ultralytics ObjectCounter with a YOLO11 nano model, labeled a single image with SAM 2, and trained it.

That one frame was enough for the system to track every potato in the entire video.

This is a solid reminder of what real industrial Al looks like. Simple. Efficient. Built for one clear job.

These focused systems save time, cut errors, and work without big infrastructure. In other words, this is the future!

#ai #physicalai

Holly s****

Do you know how long did it take to me to solve this integral I just wrote in a piece of paper?

2 secs by using this prompt: re-generate the image including the solution of the integral step by step.

I know, you must believed actually I solved the problem by myself but I didn’t… AI did it for me.

Then of course I asked for the detailed explanation with the logic on how to solve it. The goal is not to have the solution but to understand how to do it.

We humans usually have very short memory but this would have been crazy only 2 years ago…So for the ones who believe this is just another trend, trust me, this is not.

Imagine how a kid in the middle of Africa, without resources, can learn now mathematics. And take this to every single aspect of our lives.

Love it!!!!

#ai #genai

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