Config at MongoDB Shares Why Neurodiversity Matters

After a guest speaker from AsIAm visited our Dublin office in 2022, a few MongoDB employees realized there was a need for a global employee resource group (ERG) focused on disability and neurodiversity at MongoDB. This group of employees brainstormed and gathered information for a few months, contributing to a defined strategy for our new ERG, Config (a play on the word “configuration” and a nod to the database industry). Config officially launched in April 2023 with an AsIAm speaking event held in our Dublin office – the same organization that inspired the group’s formation the previous year.

Neurodiversity in the workplace

Recognizing neurodiversity within the scope of diversity and inclusion initiatives is a crucial aspect of modern workplace diversity efforts. It promotes a more inclusive environment where individuals with diverse neurological profiles, such as autism, ADHD, or dyslexia, feel valued and included in the workplace.

Neurodiversity can manifest in various ways and may show up as communication differences, sensory sensitivities, attention to detail, and unique approaches to problem-solving. Some neurodivergent individuals may have challenges with verbal communication or understanding non-verbal cues while others might excel in written communication or have a unique communication style. Sensory sensitivities can bring discomfort in environments with bright lights, loud noises, or strong odors. Also, many neurodivergent individuals thrive on routine and predictability, seeking consistent work schedules and clear expectations.

How to create an inclusive environment

In regard to recruitment and hiring, actively seeking neurodiverse talent through partnerships with neurodiversity-focused organizations, job boards, and outreach programs contributes to building a diverse workforce. On top of that, it’s important to educate recruiters and interviewers about neurodiversity to ensure they understand and appreciate different cognitive profiles and can create an inclusive interview process.

Alternative interview formats can provide a more accurate assessment of a candidate’s abilities, and structured interview questions and clear instructions help to reduce ambiguity during interviews. Allow candidates to choose interview settings that are comfortable for them, such as in-person, video, or written formats.

With workplace support, consider establishing mentoring programs to help neurodivergent employees navigate the workplace and build social connections. Work to create a sensory-friendly environment, clear communication, flexibility, and supportive supervision. In helping employees to become more supportive of their neurodivergent peers, create Neurodiversity Training to raise awareness about neurodiversity and promote a more inclusive culture. Peer Support Networks are also helpful for neurodivergent employees to share experiences and advice.

Some reasonable accommodations to consider are individual accommodation plans, quiet spaces for those who need a break from sensory stimuli, task modifications, and communication aids.

By implementing these accommodations and support structures, employers can create a more inclusive and supportive environment for neurodivergent employees, enabling them to thrive and contribute to their unique talents.

Config members share their stories

Supporting my neurodiverse family

Yair Bar (He/Him), Escalation Manager

Four out of my five children are neurodiverse: two have ADHD and two are on the autism spectrum. I've gained a deep understanding of their employment challenges once they become adults, and these barriers often stem from our neurotypical society's lack of understanding, empathy, and flexibility.

Photo of Yair and his family

Workplaces must proactively create inclusive environments for neurodivergent individuals not only to participate but also thrive. My children have taught me valuable life lessons, like resilience and embracing diversity. My experience as a parent and my awareness of neurodiversity have helped me hone my skills including empathy, encouragement, active listening, and helping individuals redefine their vision and goals.

I've applied this perspective in my career and value neurodiverse talent on my team. I firmly believe that organizations should prioritize supporting neurodiversity as it aligns with important values like commitment, social mobility, equality, and personal growth. As neurodiverse populations grow, organizations must address their specific needs.

My goal is to support those facing neurodiversity challenges, making a real difference in their lives. I aim to raise awareness about neurodiversity within and beyond MongoDB, and I aspire to contribute to a more inclusive and understanding environment where everyone's unique abilities are celebrated.

My personal experience with neurodiversity

Rachelle Green (She/They), Workplace Coordinator

Prior to 2022, I was not familiar with the concept of neurodiversity. It was through social media that I came across the term, sparking a process of self-reflection. I began to analyze my relationships, cognitive processes, organizational strategies, and sense of belonging in different communities and spaces.

In 2023, I made a conscious decision to prioritize my mental health and investigate any concerns or suspicions I had. My goal now is to focus on understanding myself better, maintaining my well-being, and fully embracing my neurodiversity.

In my journey, I’ve come to appreciate the importance of organizations embracing neurodiversity in their diversity, equity, and inclusion initiatives. By doing so, they not only foster a more inclusive environment but also tap into a wider talent pool that includes individuals with unique perspectives and exceptional abilities.

Config at MongoDB creates a space where neurodivergent thinkers like myself can feel valued and supported. I am eager to contribute my skills and experiences to this cause and make a meaningful impact in promoting neurodiversity acceptance and support within the workplace.

An ally for the neurodiverse community

Boris Subotic (He/Him), Employee Experience Manager

In my HR career, I've witnessed the valuable contributions of neurodiverse individuals, including problem-solving skills, attention to detail, and innovative thinking. I'm committed to advocating for neurodiversity at MongoDB, ensuring all employees, regardless of their neurological differences, feel supported and valued. This fosters a culture of acceptance and enhances productivity and innovation.

Recognizing neurodiversity aligns with MongoDB's value “Embrace the Power of Differences”. As an HR professional, I aim to be an ally and influencer in shaping company policies and initiatives.

I prioritize empathy and understanding, offering mentorship and professional development opportunities. Creating a supportive environment is key to ensuring everyone thrives. I'm enthusiastic about the role of Config in promoting diversity and inclusion. Collaborating with peers and implementing change initiatives can make a significant impact.

I'm excited to continue advocating for inclusivity, challenging stereotypes, and unlocking the potential of all employees through Config.

We’re committed to creating an inclusive and equitable environment for everyone. Learn more about diversity and inclusion initiatives at MongoDB.

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New Regulations Set to Snare Data-Handlers into Compliance

Now that the General Data Protection Regulation (GDPR) has become more firmly entrenched in the EU, several states in the U.S. are introducing similar data governance measures that will impose extra obligations on businesses that handle consumer data in those jurisdictions. California, Colorado, Connecticut, Utah, and Virginia all have new or amended data consumer privacy laws that have already gone into effect or are expected to by year's end. Control vs. controllers While most data privacy laws focus on giving consumers greater insight and control over their personal data, they also require data controllers and processors to protect the security and integrity of the data they handle for consumers. All five new state privacy laws require data controllers and processors to protect the information they process with reasonable data security measures. What constitutes reasonable remains up for debate, but recent trends point toward an information security program that goes beyond current requirements for safeguards and advocates for a more strategic approach based on risk assessment. Sectors like financial services and healthcare have long been accustomed to mandatory data security measures since both industries are subject to regulatory regimes — the Gramm-Leach-Bliley Act (GLBA), Financial Industry Regulatory Authority (FINRA), and the Payment Card Industry (PCI) for financial institutions, and the Health Insurance Portability and Accountability Act (HIPAA) for healthcare organizations. But gradually, the expansion of existing regulations and the introduction of new privacy laws at the state level are snaring more businesses that seek to do business in those jurisdictions. First, in 2013, the Omnibus Rule expanded the definition of a “business associate” to include all entities that create, receive, maintain, or transmit patient data on behalf of a covered entity as defined by HIPAA. So, businesses that were not previously subject to HIPAA requirements became bound by its requirements for safeguarding protected health information (PHI) if they had any in their systems or if they committed any transactions involving PHI. The Omnibus Rule was an early indicator that regulatory bodies would be casting a wider net to include not just traditional industry organizations but also data handlers that sat squarely in the middle of the data supply chain. Now, with more state consumer data privacy laws rolling out, more businesses will be required to implement reasonable security safeguards to protect any sensitive data anywhere in their systems. What's reasonable security? The National Institute of Standards and Technology (NIST) Cybersecurity Framework helps organizations better understand, manage, and mitigate cybersecurity risks. It encourages adaptability in the face of an evolving threat landscape, and the importance of data resilience measures to ensure the protection of critical assets and information. It's widely adopted across several industries for strengthening cybersecurity practices. The Center for Internet Security (CIS) also publishes examples of security controls that some state attorneys general specify as meeting a minimum level of information security that data handlers should meet. One of the universal threads running through most cybersecurity frameworks like those from NIST and CIS is the importance of data resilience. Data resilience is crucial because it ensures that important personal data like patient health records and bank customers' financial records remain available and intact, even in the face of unexpected events, such as hardware failures, cyberattacks, or natural disasters. It safeguards business continuity, preserves information integrity, and maintains trust by reducing the risk of data loss or downtime. Aside from the reputational harm that comes from being the victim of a cybersecurity event like a ransomware attack or data breach, there's an increasing risk that affected businesses will be subject to regulatory enforcement in the form of fines for running afoul of new restrictions. Security features and controls in MongoDB At MongoDB, we are intimately familiar with technical safeguards related to sensitive data and regulatory requirements as they relate to data security. MongoDB Atlas is designed for the needs of businesses in regulated industries. Atlas is a global, multi-cloud application data platform built around a resilient, performant, and scalable distributed database designed to ensure important data remains intact and available. Atlas is architected to provide automated database resilience and mitigate the downtime risks associated with hardware failures, unintended actions, and targeted attacks. Atlas clusters offer continuous cloud backups and multi-region clusters for database redundancy as well as multi-cloud clusters for cross-cloud database resilience. Atlas automatically distributes data across clouds based on how you've configured it, making managing multi-cloud clusters extremely easy. Multi-cloud cluster deployments are particularly relevant for organizations that must comply with data sovereignty regulations but have limited deployment options due to sparse regional coverage from their primary cloud provider. With MongoDB Atlas, administrators can encrypt MongoDB data in transit over the network and at rest in permanent storage and backups. For data in transit, support for TLS allows clients to connect to MongoDB over an encrypted channel. Data is automatically encrypted while at rest through transparent disk encryption at all three major cloud providers, AWS, Google Cloud, and Microsoft Azure. Additionally, MongoDB’s in-use encryption technologies like client-side Field-Level Encryption (FLE) and Queryable Encryption enable administrators to selectively encrypt sensitive fields, with each optionally secured with its own key. All encrypted fields on the server – stored in-memory, in system logs, at-rest, and in backups – are rendered as ciphertext, making them unreadable to any party and are only decrypted on the client side using the encryption keys. MongoDB also offers a complete set of administrative features that enable organizations to create, deploy, and manage policies for data access according to their own internal requirements, including database authentication, multi-factor authorization (MFA), and role-based access controls (RBAC). Of course, no business wants to lose data, and every business would prefer to avoid the reputational harm that comes from data breaches having data held for ransom. With the potential for hefty fines for running afoul of new privacy legislation, businesses have even more reasons to implement protective measures to ensure the resilience of their systems. As regulatory creep continues to expand across the data landscape, businesses must take it upon themselves to ensure data integrity and resilience are high priorities across the organization. For more information on data resilience features in MongoDB Atlas, download our Data Resilience Strategy with MongoDB Atlas whitepaper.

October 24, 2023
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Building AI With MongoDB: Integrating Vector Search And Cohere to Build Frontier Enterprise Apps

Cohere is the leading enterprise AI platform, building large language models (LLMs) which help businesses unlock the potential of their data. Operating at the frontier of AI, Cohere’s models provide a more intuitive way for users to retrieve, summarize, and generate complex information. Cohere offers both text generation and embedding models to its customers. Enterprises running mission-critical AI workloads select Cohere because its models offer the best performance-cost tradeoff and can be deployed in production at scale. Cohere’s platform is cloud-agnostic. Their models are accessible through their own API as well as popular cloud managed services, and can be deployed on a virtual private cloud (VPC) or even on-prem to meet companies where their data is, offering the highest levels of flexibility and control. Cohere’s leading Embed 3 and Rerank 3 models can be used with MongoDB Atlas Vector Search to convert MongoDB data to vectors and build a state-of-the-art semantic search system. Search results also can be passed to Cohere’s Command R family of models for retrieval augmented generation (RAG) with citations. Check out our AI resource page to learn more about building AI-powered apps with MongoDB. A new approach to vector embeddings It is in the realm of embedding where Cohere has made a host of recent advances. Described as “AI for language understanding,” Embed is Cohere’s leading text representation language model. Cohere offers both English and multilingual embedding models, and gives users the ability to specify the type of data they are computing an embedding for (e.g., search document, search query). The result is embeddings that improve the accuracy of search results for traditional enterprise search or retrieval-augmented generation. One challenge developers faced using Embed was that documents had to be passed one by one to the model endpoint, limiting throughput when dealing with larger data sets. To address that challenge and improve developer experience, Cohere has recently announced its new Embed Jobs endpoint . Now entire data sets can be passed in one operation to the model, and embedded outputs can be more easily ingested back into your storage systems. Additionally, with only a few lines of code, Rerank 3 can be added at the final stage of search systems to improve accuracy. It also works across 100+ languages and offers uniquely high accuracy on complex data such as JSON, code, and tabular structure. This is particularly useful for developers who rely on legacy dense retrieval systems. Demonstrating how developers can exploit this new endpoint, we have published the How to use Cohere embeddings and rerank modules with MongoDB Atlas tutorial . Readers will learn how to store, index, and search the embeddings from Cohere. They will also learn how to use the Cohere Rerank model to provide a powerful semantic boost to the quality of keyword and vector search results. Figure 1: Illustrating the embedding generation and search workflow shown in the tutorial Why MongoDB Atlas and Cohere? MongoDB Atlas provides a proven OLTP database handling high read and write throughput backed by transactional guarantees. Pairing these capabilities with Cohere’s batch embeddings is massively valuable to developers building sophisticated gen AI apps. Developers can be confident that Atlas Vector Search will handle high scale vector ingestion, making embeddings immediately available for accurate and reliable semantic search and RAG. Increasing the speed of experimentation, developers and data scientists can configure separate vector search indexes side by side to compare the performance of different parameters used in the creation of vector embeddings. In addition to batch embeddings, Atlas Triggers can also be used to embed new or updated source content in real time, as illustrated in the Cohere workflow shown in Figure 2. Figure 2: MongoDB Atlas Vector Search supports Cohere’s batch and real time workflows. (Image courtesy of Cohere) Supporting both batch and real-time embeddings from Cohere makes MongoDB Atlas well suited to highly dynamic gen AI-powered apps that need to be grounded in live, operational data. Developers can use MongoDB’s expressive query API to pre-filter query predicates against metadata, making it much faster to access and retrieve the more relevant vector embeddings. The unification and synchronization of source application data, metadata, and vector embeddings in a single platform, accessed by a single API, makes building gen AI apps faster, with lower cost and complexity. Those apps can be layered on top of the secure, resilient, and mature MongoDB Atlas developer data platform that is used today by over 45,000 customers spanning startups to enterprises and governments handling mission-critical workloads. What's next? To start your journey into gen AI and Atlas Vector Search, review our 10-minute Learning Byte . In the video, you’ll learn about use cases, benefits, and how to get started using Atlas Vector Search.

April 25, 2024