Graft

If you don't have time to read Your Company is Made out of Meat*, may I suggest listening to this podcast about it? https://lnkd.in/eqGFpA7A Bots may not yet know how to pronounce my last name, but they’ve made huge strides on friendly banter sprinkled with insightful commentary. Worth a listen just for the wow-factor of a generated podcast. * https://lnkd.in/gncjcbAg

The future of work is the intelligence layer, not assistants. That’s why we built Graft! If you want to know what that is and why it’s inevitable, read on… https://lnkd.in/gncjcbAg #graft #ai #intelligencelayer

Recently, a flurry of people have complained that they aren't seeing the ROI from AI. There are two possibilities: 1. The technology cannot produce the desired outcomes. 2. They are using it wrong. We know the first option is incorrect, because there are countless examples of companies using AI to improve operational efficiency, generate new revenue, and build innovative products. So, how are people using it wrong? Here are some of the most egregious errors I've seen: 1. Slapping a simple RAG pipeline on an LLM without any other supporting infrastructure or integrations; 2. Fine-tuning a model as a first step rather than an optimization step, performed after they've seen ROI; 3. Extremely narrow use cases that don't account for how they interact with broader tasks or workflows; 4. Building interfaces that fail to produce necessary behavioral changes because they were designed to be marketed, not used; and 5. Reinforcing data silos with intelligence silos, producing AI tools that are just as myopic as the people they are meant to assist. Not seeing ROI from a bad application of AI doesn't disprove its value any more than a poorly designed website disproves the value of the internet. At Graft, we built the Intelligence Layer based on our collective experience driving real business outcomes. If you want to see ROI from AI, we can help.

Graft has been recognized as one of the  Top Artificial Intelligence Solutions Provider By CIO Applications. Graft's Intelligence Layer sits above your company’s information layer to help you build better products, run a more efficient business, and innovate faster. Every team member can engage with the collective intelligence of the organization, custom-tailored to your enterprise’s specific needs, ultimately accelerating your organization's growth and competitive advantage. Under the covers, the intelligence layer is a comprehensive modern AI platform, where search, predictive, and generative AI converge to drive real business outcomes. “You can focus on outcomes instead of navigating the complexity of choosing and integrating the infrastructure components; we have curated and combined premier solutions for you. There’s no longer a need to weigh the merits of various tools or question their performance— with Graft, you have the assurance of a thoroughly vetted, cohesive system,” says Adam Oliner, founder and CEO. The article will also be featured in the forthcoming special print edition on Artificial Intelligence 2024. Read More : https://lnkd.in/gSSDxTxF #DigitalTransformation #AIIntegration #BusinessInnovation #TechSolutions #ArtificialIntelligence

Under the hood, Graft is a ‘foundation model-based,’ ‘agentic,’ ‘compound AI’ system with ‘advanced RAG.’ And it had *all* of that before those terms were coined. Anyone trying to build production-grade solutions using AI, rather than toys or demos, likely did something similar. It’s just good systems engineering. I wonder which of the many capabilities that make Graft so powerful and simple to use will be next to get a shiny new buzzword from the community. 😉

Our CEO, Adam Oliner, talking about how to navigate AI buzzwords. "A positive experience with AI happens when the solutions are simple and trustworthy. Simple because most people aren’t AI experts and won’t alter their behavior just to use a new tool. Trustworthy because there’s typically already a way to solve the problem without AI, so if people are not getting better results quickly with AI, they will default to the old ways. Tools that improve existing workflows and automatically perform useful tasks that a person simply wouldn’t do otherwise, tend to be more successful."

PDF parsers are tools designed to extract and process data from PDF files. Their significance lies in the ability to automate data extraction, streamline document workflows, and enable advanced data analysis. In this guide, Eugene Druzhynin explores 10 prominent PDF parsers, each with unique capabilities, helping you understand their functionalities and choose the right one for your needs. https://lnkd.in/grZD-PBM

Thanks Sapphire Ventures for including us in your GenAI App Infrastructure Stack!

As LLMs proliferate in enterprise search, the issue of search results reliability becomes particularly critical. One potential solution to mitigate against hallucinations is RAG (Retrieval Augmented Generation), an AI framework that enhances the quality and relevance of generated text. Hear about the latest developments in this webinar!

The problem of hallucinations, false information, and fabricated data is well known to searchers. It puts people off from trusting search results when generative AI is involved. As LLMs proliferate, not only in the open web search world but also in enterprise search, the issue of search results reliability becomes particularly critical. One potential solution to mitigate against hallucinations is RAG (Retrieval Augmented Generation), an AI framework that enhances the quality and relevance of generated text. Join Adam Oliner to hear about the latest developments in this webinar. https://lnkd.in/gTwaUFs4