Accelerate institutional knowledge transfers, procurements and sales 10X with human supervised AI assistants

Generative AI has been heralded as a revolutionary force in enterprise operations, offering the tantalizing promise of automating everything from knowledge search, summarization, multimodal content creation to customer engagement. But the reality is a lot more complex and, at times, downright messy. The rise of Retrieval-Augmented Generation (RAG) systems has brought with it a host of challenges that threaten to derail the very progress they were supposed to advance. As enterprises confront the pitfalls of RAG — context confusion, inaccurate outputs, and disjointed narratives — they must also face a hard truth: human oversight is not just important, it’s essential.

RAG systems were supposed to be the ultimate hybrid solution, combining the creative fluency of generative AI with the factual precision of retrieval systems. But in practice, they often fail where it matters most: maintaining context across multiple datasets. Enterprises, in their quest for automation, are discovering that RAG’s inability to seamlessly integrate information from diverse sources is more than a minor glitch — it’s a critical failure.

RAG struggles to see the full context for a human query

Consider a global enterprise generating a high-stakes financial report using a RAG system. The model pulls data from various sources — some of it outdated, some of it contextually irrelevant — and weaves it together into a document that’s less a cohesive analysis and more a patchwork of conflicting information. This isn’t just an embarrassment; it’s a potential disaster for decision-making at the highest levels.

The solution to these failings isn’t to abandon RAG altogether but to recognize its limitations and ensure that humans remain firmly in the loop. Automated systems, no matter how advanced, lack the nuanced understanding that humans bring to the table — especially in contexts where the stakes are high and the data is complex.

Human oversight is crucial for several reasons. First, humans can catch the subtle inconsistencies and errors that a RAG system might overlook. When generating mission-critical content, such as regulatory filings, legal documents, or strategic business reports, the risks of relying solely on AI are simply too great. A human editor can review the AI’s output, ensuring that the information is not only accurate but also contextually appropriate and aligned with the broader objectives of the enterprise.

Second, humans can guide the AI by reinforcing correct outputs and correcting errors — a process known as reinforced learning. By actively engaging with the system, human operators can help the AI learn from its mistakes, gradually improving its performance over time. This is particularly important in environments where the data is constantly evolving, and the AI must adapt to new information quickly.

To mitigate the risks associated with RAG, enterprises should invest in creating a user experience that integrates human feedback loops and reinforced learning mechanisms. This approach not only keeps humans in the loop but also leverages their input to make the AI smarter and more reliable.

For example, an enterprise could implement a RAG-based system where every generated output is first reviewed by a human. The human reviewer can flag errors, suggest improvements, and provide feedback that the AI uses to refine its future outputs. This iterative process helps build a more robust and contextually aware AI, one that can better handle the complexities of enterprise data.

AI agents need their human masters to make them work effectively

Moreover, enterprises can enhance the creative user experience by designing interfaces that allow human users to interact more intuitively with RAG systems. Instead of treating the AI as a black box, these interfaces can give users greater control over the retrieval and generation processes. This could involve allowing users to specify the context or domain from which information should be retrieved, or enabling them to tweak the AI’s generative parameters to better match their needs.

Generative AI, especially when paired with retrieval systems, has incredible potential to transform enterprise operations. But as RAG systems currently stand, they are far from foolproof. Context collapse, retrieval inaccuracies, and the sheer complexity of managing these systems reveal the critical need for human oversight.

The future of enterprise AI isn’t one where machines operate in isolation but rather where they work in concert with humans. By keeping humans in the loop and designing systems that incorporate creative user experience and reinforced learning, enterprises can harness the power of RAG without falling prey to its pitfalls. This human-AI partnership is not just a safeguard against failure; it’s the key to realizing the full potential of generative AI in the enterprise.

Adam Hoey — Senior Advisor

March 5, 2024

In the intricate ecosystem of modern enterprises, institutional knowledge serves as the cornerstone of sustained success. However, when seasoned employees retire or depart, they take with them a wealth of expertise, insights, relationships and institutional memory, leaving behind a void that can prove costly for the organization. On top of that workplace tenure has decreased on average.

According to a report by the American Productivity & Quality Center (APQC), “Organizations lose 45% of their institutional knowledge every time an employee leaves.” This loss extends beyond mere data or documents; it encompasses the intricate understanding of processes, relationships, and organizational dynamics that can’t be easily quantified.

Financially, the toll can be substantial. According to an analysis by Panopto in an interview with HR Daily Advisor they calculated “ ..the average U.S. enterprise-size business may be wasting $4.5 million in productivity annually just due to failing to preserve and share knowledge and thereby, making new hire onboarding more inefficient.”

The Society for Human Resource Management (SHRM) notes, “The cost of replacing an employee can range from one-half to two times the employee’s annual salary.” This includes expenses related to recruitment, onboarding, training, and the inevitable dip in productivity as new hires acclimate to their roles.

Moreover, the loss of institutional knowledge can disrupt workflow, impede decision-making, and compromise service quality. As Dr. Christina Ellwood, a researcher in organizational behavior, emphasizes, “The departure of experienced employees often leads to increased errors, delays, and inefficiencies, as their replacements struggle to replicate their level of expertise.”

Within the context of the US Federal Government for example, consider the Federal Acquisition Regulation (FAR) — an intricate regulation used by executive agencies for procurements and the acquisition of supplies and services can take years to master. Loss of knowledge can increase contract errors that can dramatically slow down cycle times or even worse completely derail a project which in order to be successful would have required intricate knowledge of allowable exceptions to reduce the regulatory burden. With significant numbers of retirements expected, agencies are scrambling to drive employee mentoring programs to document and transfer this institutional knowledge.

Enter Generative Artificial Intelligence (GenAI), a transformative force poised to reshape how enterprises manage and leverage institutional knowledge. By deploying AI-driven knowledge management systems, organizations can capture, organize, analyze and share vast troves of data with unprecedented speed and accuracy.

AI-powered solutions offer intelligent search capabilities, enabling employees to quickly access relevant information and insights buried within mountains of data. Furthermore, AI-driven virtual assistants can serve as virtual mentors, guiding employees through complex tasks and providing real-time support. AI facilitates knowledge sharing and collaboration across departments and geographical locations.

With Knowledge AI from Morfius, knowledge workers can get quick access to accurate and personalized AI answers to complex questions from private enterprise documents, data, media catalogs and knowledge bases. Public sector and enterprise can leverage Knowledge AI to retain institutional knowledge, speed onboarding and tackle common business challenges.

In essence, AI acts as a force multiplier, augmenting human capabilities and mitigating the impact of losing institutional knowledge. As businesses navigate an era of unprecedented change and disruption, leveraging GenAI to preserve and harness organizational wisdom isn’t just a competitive advantage — it’s an imperative for long-term success.

Let’s talk GenAI for government and enterprise. contact@morfius.ai

ERIK SWENSSON, MORFIUS VICE PRESIDENT

Feb 28, 2024

The federal procurement process can be tedious and time-consuming, as each acquisition must comply with the Federal Acquisition Regulation (FAR) a complex regulation over two thousand pages long. From soliciting bids to negotiating and awarding contracts, it often takes agencies months or even years to acquire goods and services. Moreover, it takes years or even decades to master the intricacies of the FAR and contract development where tribal subject matter knowledge can be instantly lost with staff retirements and departures. The White House states that there are over 400,000,000 contracts and orders a year placed by the federal government. So the number of hours and time spent in this process is staggering.

However, new advances in generative artificial intelligence (Gen AI) present an opportunity to significantly shorten procurement cycles. Generative AI applications like Morfius’s Procurement AI can now write coherent long-form text and be trained and tuned on FAR and specific agency requirements, in a safe privately hosted environment. These applications can even search meeting transcripts for requirements, scope, and details to help federal buyers generate initial drafts of government contracts and requests for proposals (RFPs). Instead of starting from scratch, federal employees and contractors can now use safe, secure, and explainable AI assistants to put together an initial document that covers all the necessary terms, clauses, and standards based on procurement requirements. This will give them a strong foundation to build upon rather than having to write contracts fully manually.

Morfius has government agencies finding they can save not only half the time it takes to produce a complaint document but also shave weeks off of the procurement cycle, and reduce errors in the process. In this case, it’s not replacing the need for government employees, but rather it allows them to reduce time spent on tedious tasks, freeing them to focus on their agency’s mission.

ERIK SWENSSON, VP SALES

Feb 07, 2024

The “should I build or buy” software decision has been one organizations have faced for decades. Companies must ask themselves, should they utilize their development efforts on an application or buy something already built for this purpose and focus resources on a different and more impactful problem. Typically companies put development ‘build’ resources on projects that off-the-shelf software cannot supply, where complex business or regional regulatory requirements exist and for items that will truly differentiate them from their competitors. Back-office, productivity, and security products typically fall into this ‘buy’ category.

Generative AI applications promise to bring new capabilities and efficiencies to businesses. While legacy off-the-shelf applications may offer new AI features, companies may still have the need to build tailored AI applications in-house to satisfy niche business needs. However, developing custom generative AI requires significant data science resources — which are in high demand and limited supply — alongside development resources. This scarcity puts a twist on the traditional build vs buy software decision. Data scientists are considered far more scarce than development resources. In fact, insufficient data science talent is a top barrier to the technology’s adoption, according to Anaconda’s “State of Data Science 2022 report”. Unlike traditional software, quality generative AI relies heavily on curated datasets, robust models, and continual tuning from experienced data scientists.

With the global shortage of data science talent, developing custom generative applications risks diverting valuable data scientists away from high-impact business projects. Attempting to build generics generative apps in-house could delay other data initiatives that more directly impact core operations and strategic goals.

Utilizing off-the-shelf natively designed Generative AI applications such as Digital Tutor and Knowledge AI for training, onboarding, and knowledge management can lower the cost of development and increase time-to-value. Companies can put to use built and tested applications like Procurement AI to build contracts and reduce procurement times. This will allow you to focus Data Science Efforts on high-impact or regulated areas within your business. Their time is best focused on developing generative applications that generate a long-term competitive advantage or enable wholly new business capabilities.

At MORFIUS, we create generative AI applications for enterprises, unlocking the power of structured and unstructured knowledge bases to develop robust, groundbreaking enterprise AI solutions. Our mission? Help organizations rapidly design, pilot, and deploy Generative AI apps that solve business problems, create higher productivity, and lower costs.
Our Origin & Values

MORFIUS began with a handful of AI industry experts, data scientists, and software engineers in the U.S., India, and Brazil who shared a passion for AI and were brimming with ideas to create ways to leverage Generative AI’s power in the enterprise efficiently.

Today, we are a growing team of technical and business leaders committed to our values of keeping the power of Generative AI as accessible, safe, and secure, given the furious pace of innovation and increasing complexity of the AI space.

We at MORFIUS are excited to be on our journey into the future of enterprise AI, bringing our vision and innovative solutions to the forefront of the industry. Join us in this exciting venture as we redefine what’s possible in enterprise AI applications.

Who We Are
MORFIUS isn’t about developing new foundational AI models or generic development tools. With the fast-changing pace of technology, we aim to evaluate, optimize, and scale existing AI tools using our unique architectural framework and processes.

We believe in the power of “small” generative AI models for enterprise solutions, dispelling the myth that bigger is always better. Our models are designed to solve enterprise challenges faster and more cost-effectively.

Benefits & Value to Enterprise
Morfius combines technical innovation with tangible business benefits, enhancing productivity and scaling business objectives and KPIs. We focus on key performance indicators demonstrating the immediate advantages of generative AI for our customers.

We focus (obsess even!) on making the customer journey easier with:

● Development Speed: Unmatched development speed for AI products and solutions. Create a functional application in minutes for stakeholder presentations.
● Cost of AI Training: Lower development and AI training expenses. Our Retrieval Augmented Generation (RAG) based approach results in a more than 100-fold decrease in AI training costs.
● AI Accuracy: Enhanced contextual accuracy in responses to human queries, thanks to our RAG and advanced summarization/reasoning algorithms.
● User Adoption: Prioritizing human-centric design, our apps, and UX are consistent and cater to non-technical business users, broadening AI accessibility significantly. Responses are easily sourced and integrated into reports visualization workflows.
Ease of Administration: Platform and app admins have a unified interface to manage business applications, logs, KPIs, and user access security.
● Enhanced Security and Privacy: Ensuring robust enterprise security, AI safety, and privacy, our platform upholds the highest standards for data protection and ethical AI usage.

MORFIUS Platform, Architecture, and Process Overview

MORFIUS’s platform and architecture are innovatively designed with a generative AI-first approach, discarding traditional software development and runtime models. We’ve integrated cutting-edge techniques and strategies from the latest AI advancements into our core technical features.

Our modular architecture makes it easy to spin up enterprise pilots and tailor foundational components such as large language models, vector databases, and cloud hosting providers.

● RAG-Based Knowledge Search: Leveraging vector databases and retrieval augmented generation (RAG), our approach transforms AI training economics, ensuring more accurate, relevant, and sourced AI responses for enterprise applications.
● Knowledge Summarization and Reasoning: We enhance answer accuracy in enterprise-focused applications by integrating large language model (LLM) summarizations and reasoning.
● App Regeneration: Our platform automates the deployment of secure enterprise applications through regenerative technology.
● AI Security and Safety: We emphasize comprehensive security measures, including access controls, admin delegation, data, and content security, AI transparency, explainability, and user-friendly interfaces for business efficiency.

Our Apps and The Future of Knowledge Automation

MORFIUS applications automate knowledge capture, synthesis, and distribution within enterprise workflows. Digital Tutor and Procurement AI are our latest apps with more business innovations on the roadmap (Migration AI, Inventory AI, Grants AI and more).

The Digital Tutor app, available now on Google Cloud Marketplace, is a versatile generative AI tool for knowledge management across various organizations, including corporations, governments, and educational institutions. It revolutionizes learning by allowing complete control over content, answers, and user experiences.

With Procurement AI, we help procurement analysts and contract managers streamline workflows and gain valuable new insights, predictions, patterns, and visualizations.

We are a collective of innovators and problem-solvers dedicated to transforming the landscape of enterprise AI applications. Our journey is marked by a commitment to our vision, a focus on groundbreaking innovations, and a steadfast dedication to our customers’ needs. As we move forward, we’re not just aiming to be a part of the industry — we’re striving to lead it, shaping the future of enterprise AI with solutions that are not only technologically advanced but also ethically responsible, user-friendly, and profoundly impactful.

Washington, DC, and San Francisco, CA [Jan 18th, 2024]

Morfius Inc., a leader in personalized generative AI applications for enterprises, is excited to join the Google Cloud Partner Advantage program as an ISV and Build Partner. Our debut product, MORFIUS Digital Tutor, is now available on Google Cloud Marketplace. This collaboration introduces Google Cloud customers to a pioneering suite of enterprise applications featuring native generative AI, revolutionizing user experiences and economic models.

Morfius Value And Benefits For Enterprise

Morfius combines technical innovation with tangible business benefits, enhancing productivity and scaling business objectives and KPIs. Our focus is on key performance indicators that demonstrate the immediate advantages of generative AI for our customers:

• Development speed: Unmatched development speed for AI products and solutions. Create a functional application in minutes for stakeholder presentations.
• Cost of AI training: Lower development and AI training expenses. Our Retrieval Augmented Generation (RAG) based approach that results in a more than 100-fold decrease in AI training costs.
• AI accuracy: Enhanced contextual accuracy in responses to human queries, thanks to our RAG and advanced summarization/reasoning algorithms.
• User adoption: Prioritizing human-centric design, our products cater to non-technical business users, broadening AI accessibility significantly.
• Enhanced security and privacy: Ensuring robust enterprise security, AI safety, and privacy, our platform upholds the highest standards for data protection and ethical AI usage.

“We are excited to join the Google Cloud Partner Advantage program as an ISV partner available on Google Cloud Marketplace. It is not just a step forward for MORFIUS but a leap forward for the personalized generative AI applications market. We are hoping to be a catalyst for it,” said Hamza Jahangir, CEO and Founder of Morfius. “Our collaboration is founded on a shared vision of making AI not just technologically advanced but also personal, safe, and optimally integrated into the enterprise fabric.”

MORFIUS leverages Google Cloud to offer advanced, user-friendly, generative AI applications for enterprises. These apps are designed for easy deployment, efficient AI training, and scalability. They combine the power of language models with features essential for accuracy, security, and cost-effectiveness, ensuring smooth integration into enterprise systems.

Our innovative MORFIUS runtime framework significantly shortens the time to market by quickly regenerating pre-trained applications. It employs AI automation to create comprehensive tech stacks from simple natural language inputs, including tailored user interfaces and workflows. This efficient process maintains critical enterprise standards for security, governance, and privacy without necessitating a rebuild of the foundational elements.

MORFIUS Digital Tutor

The Digital Tutor app, available now on Google Cloud Marketplace, is a versatile generative AI tool for knowledge management across various organizations, including corporations, governments, and educational institutions. It revolutionizes learning by allowing complete control over content, answers, and user experiences.

MORFIUS Platform, Architecture, and Process Overview

MORFIUS’s platform and architecture are innovatively designed with a generative AI-first approach, discarding traditional software development and runtime models. We’ve integrated cutting-edge techniques and strategies from the latest AI advancements into our core technical features.

• RAG-Based Knowledge Search: Leveraging vector databases and retrieval augmented generation (RAG), our approach transforms AI training economics, ensuring precise AI responses for enterprise applications.
• Knowledge Summarization and Reasoning: We enhance answer accuracy in enterprise-focused applications by integrating large language model (LLM) summarizations and reasoning.
• App Regeneration: Our platform automates the deployment of secure enterprise applications through regenerative technology.
• AI Security and Safety: We emphasize comprehensive security measures, including access controls, admin delegation, data and content security, AI transparency, explainability, and user-friendly interfaces for business efficiency.

Enterprises looking to harness the power of personalized AI are invited to explore Morfius’s solutions on Google Cloud Marketplace here.

About Morfius:

Morfius is at the forefront of Generative AI technology and is dedicated to developing apps that are not only productive but also personal and secure. With a focus on enterprise needs, Morfius is redefining how businesses interact with AI, ensuring every solution is as responsible as it is revolutionary. For more information, please visit www.morfius.ai.