Surojit Chatterjee is the founder and CEO of Ema. Beforehand, he guided Coinbase by means of a profitable 2021 IPO as its Chief Product Officer and scaled Google Cellular Advertisements and Google Procuring 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 aim for Ema is obvious and daring: “transform enterprises by building a universal AI employee.” This imaginative and prescient stems from our perception that AI can increase human capabilities slightly than change employees completely. Our Common AI Worker is designed to automate mundane, repetitive duties, liberating up human staff to concentrate on extra strategic and useful work. We do that by means of Ema’s revolutionary agentic AI system, which may carry out a variety of complicated duties with a group of AI brokers (referred to as Ema’s Personas), bettering effectivity, and boosting productiveness throughout numerous organizations.
Each you and your co-founder have spectacular backgrounds at main tech firms. How has your previous expertise influenced the event and technique of Ema?
Over the past twenty years, I’ve labored at iconic firms like Google, Coinbase, Oracle and Flipkart. And at each place, I puzzled “Why do we hire the smartest people and give them jobs that 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 adverts at Google. These experiences deepened my technical data throughout engineering, machine studying, and adtech. These roles allowed me to establish inefficiencies within the methods we work and learn how 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 knowledge, machine studying, and gadgets. Earlier than that, he was at Google, the place he was engineering lead for knowledge and machine studying the place he constructed one of many world’s largest ML programs, targeted on privateness and security – Google’s Belief Graph. His experience, significantly, is a driving pressure to why Ema’s Agentic AI system is extremely correct and constructed to be enterprise prepared by way of safety and privateness.
My cofounder Souvik and I assumed what when you had a Michelin Star Chef in-house who might cook dinner something you requested for. You may be within the temper for French right this moment, Italian tomorrow and Indian the day after. However regardless of your temper or the delicacies you want, that chef can recreate the dish of your desires. That’s what Ema can do. It could tackle the function 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 assorted sources?
LLM’s, whereas highly effective, fall quick in enterprise settings attributable to their lack of specialised data and context-specific coaching. These fashions are constructed on normal knowledge, leaving them ill-equipped to deal with the nuanced, proprietary data that drives enterprise operations. This limitation can result in inaccurate outputs, potential knowledge safety dangers, and an incapability to offer 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. Not like static LLMs, our agentic AI programs can:
- Adapt to enterprise-specific knowledge and workflows
- Leverage a number of LLMs primarily based on accuracy, price, and efficiency necessities
- Keep knowledge privateness and safety by working inside firm infrastructure
- Present explainable and verifiable outputs, essential for enterprise accountability
- Repeatedly replace and study from real-time enterprise knowledge
- Execute complicated, multi-step duties autonomously
We guarantee seamless integration from these assorted sources by utilizing Ema’s proprietary 2T+ parameter combination of specialists mannequin: EmaFusionTM. EmaFusionTM combines 100+ public LLMs and plenty of area particular customized fashions to maximise accuracy on the lowest potential price for broad number of duties within the enterprise, maximizing the return on funding. Plus, with this novel method, Ema is future-proof; we’re consistently including new fashions to forestall overreliance on one expertise stack, taking this danger away from our enterprise clients.
Are you able to clarify how the Generative Workflow Engine works and what benefits it provides over conventional workflow automation instruments?
We’ve developed tens of template Personas (or AI staff for particular roles). The personas might be configured and deployed shortly 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, corresponding to reflection, planning, instrument use, multi-agent collaboration, language agent tree search (LATS), structured output and multi-agent collaboration, and introduces many revolutionary patterns of its personal. With over 200 pre-built connectors, Ema seamlessly integrates with inner knowledge sources and might 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 progress 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 purposes resulting in knowledge and motion silos. McKinsey & Co. estimates that generative AI might 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 many of the final many years technical automations haven’t occurred because the expertise was not superior sufficient for his or her processes. That is the place we see the largest alternative for transformation and are seeing quite a lot of demand from clients in these industries to leverage Generative AI and expertise like by no means earlier than.
How does Ema tackle knowledge safety and safety considerations, particularly when integrating a number of fashions and dealing with delicate enterprise knowledge?
A urgent concern for any firm utilizing agentic AI is the potential for AI brokers to go rogue or leak non-public knowledge. Ema is constructed with belief at its core, compliant with main worldwide requirements corresponding to SOC 2, ISO 27001, HIPAA, GDPR, NIST AI RMF, NIST CSF, NIST 800-171 To make sure enterprise knowledge stays non-public, safe, and compliant, Ema has carried out the next safety measures:
- Automated redaction and secure de-identification of delicate knowledge, audit logs
- Actual-time monitoring
- Encryption of all knowledge 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 instances, lowering clients’ probability of IP liabilities. Ema additionally by no means trains fashions on one buyer’s knowledge to learn different clients.
Ema additionally provides versatile deployment choices together with on-premises deployment capabilities for a number of cloud programs, enabling enterprises to maintain their knowledge inside their very own trusted environments.
How simple 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 kind of simple. Enterprise customers can arrange Ema’s Persona(s) utilizing pre-built templates in simply minutes. They’ll advantageous tune Persona conduct with conversational directions, use pre-built connectors to combine with their apps and knowledge sources, and optionally plug in any non-public customized fashions educated on their very own knowledge. As soon as arrange, specialists from the enterprise can practice their Ema persona with only a few hours of suggestions. Ema has been employed for a number of roles by enterprises corresponding 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 consider has been the important thing to gaining such robust investor confidence?
We consider traders can see how Ema’s platform allows enterprises to make use of Agentic AI successfully, streamlining operations for substantial price reductions and unlocking new potential income streams. Moreover, Ema’s administration crew are specialists in AI and have the required technical data and talent units. We even have a robust observe report of enterprise-grade supply, reliability, and compliance. Lastly, Ema’s merchandise are differentiated from anything in the marketplace, it’s pioneering the newest 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 function of AI within the office evolving over the subsequent decade, and what function will Ema play in that transformation?
Ema’s mission is to rework enterprises and assist each worker work quicker with the assistance of simple-to-activate and correct brokers. Our common AI worker has the potential to assist enterprises execute duties throughout buyer assist, worker assist, gross sales enablement, compliance, income operations, and extra. We’d like to rework the office by permitting groups to concentrate on probably 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 staff, the place innovation prospers, and productiveness skyrockets.
Thanks for the good interview, readers who want to study extra ought to go to Ema.
