Surojit Chatterjee is the founder and CEO of Ema. Beforehand, he guided Coinbase by way of a profitable 2021 IPO as its Chief Product Officer and scaled Google Cell Advertisements and Google Buying into multi billion greenback companies because the VP and Head of Product. Surojit holds 40 US patents and has an MBA from MIT, MS in Pc Science from SUNY at Buffalo, and B. Tech from IIT Kharagpur.
Ema is a common AI worker, seamlessly built-in into your group’s current IT infrastructure. She’s designed to reinforce productiveness, streamline processes, and empower your groups.
Are you able to elaborate on the imaginative and prescient behind Ema and what impressed you to create a common AI worker?
The purpose for Ema is obvious and daring: “remodel enterprises by constructing a common AI worker.” This imaginative and prescient stems from our perception that AI can increase human capabilities reasonably than exchange staff fully. Our Common AI Worker is designed to automate mundane, repetitive duties, liberating up human workers to concentrate on extra strategic and beneficial work. We do that by way of Ema’s progressive agentic AI system, which might carry out a variety of complicated duties with a group of AI brokers (known as Ema’s Personas), bettering effectivity, and boosting productiveness throughout numerous organizations.
Each you and your co-founder have spectacular backgrounds at main tech corporations. How has your previous expertise influenced the event and technique of Ema?
Over the past twenty years, I’ve labored at iconic corporations like Google, Coinbase, Oracle and Flipkart. And at each place, I puzzled “Why will we rent the neatest folks and provides them jobs which are so mundane?.” That is why we’re constructing Ema.
Previous to co-founding Ema, I used to be the chief product officer of Coinbase and Flipkart and the worldwide head of product for cellular advertisements at Google. These experiences deepened my technical data throughout engineering, machine studying, and adtech. These roles allowed me to determine inefficiencies within the methods we work and methods to remedy complicated enterprise issues.
Ema’s co-founder and head of engineering, Souvik Sen, was beforehand the VP of engineering at Okta the place he oversaw information, machine studying, and gadgets. Earlier than that, he was at Google, the place he was engineering lead for information and machine studying the place he constructed one of many world’s largest ML programs, centered on privateness and security – Google’s Belief Graph. His experience, significantly, is a driving power to why Ema’s Agentic AI system is extremely correct and constructed to be enterprise prepared when it comes to safety and privateness.
My cofounder Souvik and I believed what in the event you had a Michelin Star Chef in-house who may prepare dinner something you requested for. You could be within the temper for French right now, Italian tomorrow and Indian the day after. However no matter your temper or the delicacies you want, that chef can recreate the dish of your goals. That’s what Ema can do. It could tackle the position of no matter you want within the enterprise with only a easy dialog.
Ema makes use of over 100 giant language fashions and its personal smaller fashions. How do you guarantee seamless integration and optimum efficiency from these diversified sources?
LLM’s, whereas highly effective, fall quick in enterprise settings because of their lack of specialised data and context-specific coaching. These fashions are constructed on common information, leaving them ill-equipped to deal with the nuanced, proprietary info that drives enterprise operations. This limitation can result in inaccurate outputs, potential information safety dangers, and an incapability to supply domain-specific insights essential for knowledgeable decision-making. Agentic AI programs like Ema tackle these shortcomings by providing a extra tailor-made and dynamic method. In contrast to static LLMs, our agentic AI programs can:
- Adapt to enterprise-specific information and workflows
- Leverage a number of LLMs based mostly on accuracy, price, and efficiency necessities
- Preserve information privateness and safety by working inside firm infrastructure
- Present explainable and verifiable outputs, essential for enterprise accountability
- Constantly replace and study from real-time enterprise information
- Execute complicated, multi-step duties autonomously
We guarantee seamless integration from these diversified sources through the use of Ema’s proprietary 2T+ parameter combination of consultants mannequin: EmaFusionTM. EmaFusionTM combines 100+ public LLMs and lots of area particular customized fashions to maximise accuracy on the lowest potential price for extensive number of duties within the enterprise, maximizing the return on funding. Plus, with this novel method, Ema is future-proof; we’re continually including new fashions to stop overreliance on one know-how stack, taking this danger away from our enterprise clients.
Are you able to clarify how the Generative Workflow Engine works and what benefits it affords over conventional workflow automation instruments?
We’ve developed tens of template Personas (or AI workers for particular roles). The personas might be configured and deployed rapidly by enterprise customers – no coding data required. At its core, Ema’s Personas are collections of proprietary AI brokers that collaborate to carry out complicated workflows.
Our patent-pending Generative Workflow Engine™, a small transformer mannequin, generates workflows and orchestration code, choosing the suitable brokers and design patterns. Ema leverages well-known agentic design patterns, akin to reflection, planning, device use, multi-agent collaboration, language agent tree search (LATS), structured output and multi-agent collaboration, and introduces many progressive patterns of its personal. With over 200 pre-built connectors, Ema seamlessly integrates with inner information sources and may take actions throughout instruments to carry out successfully in varied enterprise roles.
Ema is utilized in varied domains from customer support to authorized to insurance coverage. Which industries do you see the very best potential for development with Ema, and why?
We see potential throughout industries and features as most enterprises have lower than 30% automation in processes and use greater than 200 software program functions resulting in information and motion silos. McKinsey & Co. estimates that generative AI may add the equal of $2.6 trillion to $4.4 trillion yearly in productiveness positive factors (supply).
These points are exacerbated in regulated industries like healthcare, monetary companies, insurance coverage the place a lot of the final many years technical automations haven’t occurred for the reason that know-how was not superior sufficient for his or her processes. That is the place we see the most important alternative for transformation and are seeing loads of demand from clients in these industries to leverage Generative AI and know-how like by no means earlier than.
How does Ema tackle information safety and safety considerations, particularly when integrating a number of fashions and dealing with delicate enterprise information?
A urgent concern for any firm utilizing agentic AI is the potential for AI brokers to go rogue or leak non-public information. Ema is constructed with belief at its core, compliant with main worldwide requirements akin to SOC 2, ISO 27001, HIPAA, GDPR, NIST AI RMF, NIST CSF, NIST 800-171 To make sure enterprise information stays non-public, safe, and compliant, Ema has carried out the next safety measures:
- Automated redaction and protected de-identification of delicate information, audit logs
- Actual-time monitoring
- Encryption of all information at relaxation and in transit
- Explainability throughout all output outcomes
To go the additional mile, Ema additionally checks for any copyright violations for doc era use circumstances, lowering clients’ likelihood of IP liabilities. Ema additionally by no means trains fashions on one buyer’s information to learn different clients.
Ema additionally affords versatile deployment choices together with on-premises deployment capabilities for a number of cloud programs, enabling enterprises to maintain their information inside their very own trusted environments.
How straightforward is it for a brand new firm to get began with Ema, and what does the everyday onboarding course of appear like?
Ema is extremely intuitive, so getting groups began on the platform is sort of straightforward. Enterprise customers can arrange Ema’s Persona(s) utilizing pre-built templates in simply minutes. They’ll positive tune Persona conduct with conversational directions, use pre-built connectors to combine with their apps and information sources, and optionally plug in any non-public customized fashions educated on their very own information. As soon as arrange, consultants from the enterprise can practice their Ema persona with just some hours of suggestions. Ema has been employed for a number of roles by enterprises akin to Envoy World, TrueLayer, Moneyview, and in every of those roles Ema is already acting at or above human efficiency.
Ema has attracted vital funding from high-profile backers. What do you imagine has been the important thing to gaining such sturdy investor confidence?
We imagine traders can see how Ema’s platform permits enterprises to make use of Agentic AI successfully, streamlining operations for substantial price reductions and unlocking new potential income streams. Moreover, Ema’s administration staff are consultants in AI and have the required technical data and talent units. We even have a robust monitor file of enterprise-grade supply, reliability, and compliance. Lastly, Ema’s merchandise are differentiated from the rest in the marketplace, it’s pioneering the most recent technical developments in Agentic AI, making us the go-to alternative for any enterprise wanting so as to add next-generation AI to their operations.
How do you see the position of AI within the office evolving over the following decade, and what position will Ema play in that transformation?
Ema’s mission is to rework enterprises and assist each worker work sooner with the assistance of simple-to-activate and correct brokers. Our common AI worker has the potential to assist enterprises execute duties throughout buyer help, worker help, gross sales enablement, compliance, income operations, and extra. We’d like to rework the office by permitting groups to concentrate on essentially the most strategic and highest-value tasks as a substitute of mundane, administrative duties. As a pioneer of agentic AI, Ema is main a brand new period of collaboration between human and AI workers, the place innovation thrives, and productiveness skyrockets.
Thanks for the nice interview, readers who want to study extra ought to go to Ema.
