Seekr Technologies

Today, we're launching SeekrFlow as a complete, self-service AI platform for enterprises to build and run trusted AI applications. Enterprises can now sign up and accelerate their time to market through an intuitive user interface and new features that simplify the path to ROI: ✅ Build a production-grade LLM in 30 minutes or less.  ✅ Manage AI workflows end to end, on the infrastructure of your choice.  ✅ Generate high quality training data at up to 90% cheaper cost.  ✅ Customize models to your business needs with 3x the accuracy.  ✅ Leverage rich explainability tools to validate model accuracy.  ✅ Launch models reliably into production in five easy steps.  ✅ Low cost, usage-based pricing model and compute optimization. 🔗 Learn more about the SeekrFlow enterprise AI platform: https://bit.ly/3zbCH0R #EnterpriseAI #TrustedAI #AIDevelopment #SeekrFlow #AI

How can you efficiently build AI models that understand your industry, business, and customers? Our agentic workflow, Principle Alignment, offers a simple method to customize a foundational model to the principles of a specific domain, enabling faster data creation, enhanced model accuracy, and reduced production costs. Here's how it works: 1️⃣  Principle definition: A SeekrFlow user provides a set of high-level principles or policy documents/guidelines that they need the model to adhere to. 2️⃣ Data ingestion: An autonomous alignment workflow begins, ingesting and structuring these principles (e.g. in a hierarchical document knowledge graph) to organize it into structured data that the agentic workflow expects. 3️⃣ Data creation: The agent enters a data generation and refinement pipeline where it iteratively researches, generates, critiques, and refines the understanding of the principles. 4️⃣ Human-in-the-loop: Throughout the process, subject matter experts can iteratively provide feedback on the model's understanding of the principles to refine the generation of synthetic data and maximize accuracy. 5️⃣ The result: High-quality, domain-specific data ready for model fine-tuning 🚀

Errors in foundation models undercut AI performance in production. Hear from our President & CTO Rob Clark on the importance of prioritizing data quality and contestability to deliver trusted AI outcomes.

When trust in AI is mandatory, explainability is mandatory.    Our Chief of AI R&D Stefanos Poulis reveals the questions that enterprise leaders need to ask of their models to build reliable applications. 

#DoDIIS24 was great. Expanded how I see LLM use cases now and over time. Demand signal for LLM agents is becoming clear for use cases to help intel analysts correlate, summarize, and disseminate relevant insights. More subtly, I’ve learned with many great attendees that Seekr Technologies can help now with OSINT evaluation and exploitation. I see us filling real gaps in dynamic threat pictures, giving analysts teams of trusted, validated agents connecting dots, finding ambiguity, illuminating inference points, and challenging assumptions. It’s wonky but cool to help get clear signal on objective facts. Back to work! As the conference high wears off and next phase of investment and effort picks up, this post on the Seekr blog is my “big think” takeaway for comment here. Motivated by great conversations and new connections to fine tune and keep pushing myself #BeyondGroupthink to keep the picture clear. The threats are busy, but our best principles give us winning insights when we share a unity of purpose. LMK what you think. #GenAI #OSINT #Ontologies #Intelligence

With the official roll out of Apple Intelligence, I recently had the opportunity to share my perspective with The Drum on how forward-thinking marketers can harness these innovative AI capabilities to gain a competitive edge. As we do at Seekr Technologies, it's crucial for marketers to stay at the forefront of AI to empower our businesses with intelligent and responsible solutions that drive real results. https://lnkd.in/eSSqFB4z

An insightful deep dive from Digiday featuring our VP of Product Nick Sabharwal on the opportunities and limitations of watermarking AI-generated content. We're focused on making the web more reliable and transparent for all.

There's typically a trade-off between RAG solutions and fine-tuned models: 👉 RAG solutions are quick to deploy but come with high variable costs in production. 👉 Fine-tuned models have a high upfront cost but offer lower variable costs in the long run. Our VP of Product Nick Sabharwal explains how SeekrFlow's Principle Alignment offers the best of both, helping teams automatically create a fine-tuning dataset and launch industry-specific models at a fraction of the time and cost 🚀

How do you ensure your model performs in production? SeekrFlow's Sandbox lets you compare two models side-by-side to determine which model produces the most accurate outputs for your use case. ➡ Example: We fine-tuned a model based on an airline's policies to act as a customer service chatbot and compared its responses to a base model.    We asked both, "When is REAL ID going to be required to fly within the U.S.?" ➡ Results:  Fine-tuned model (left): Accurate, policy-compliant response ✅ Base model (right): Inaccurate with high token count ❌ For enterprise AI, optimizing model performance before deployment is critical. Explore the latest tools to enhance accuracy: https://bit.ly/3Yj9Dgy #XAI #EnterpriseAI #SeekrFlow

The AI lifecycle is complex—and expensive. 🔧 Only 15% of organizations have the infrastructure needed to support AI systems 💸 Organizations spend more than 80% of their total budget on AI infrastructure 📉 85% of AI/machine learning projects fail to produce a return for the business To unlock ROI from AI, enterprise teams must simplify operations and adopt an outcomes-first approach at every stage of the lifecycle.