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 Cellular Adverts 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 Laptop 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 evident and daring: “transform enterprises by building a universal AI employee.” This imaginative and prescient stems from our perception that AI can increase human capabilities somewhat than substitute staff solely. Our Common AI Worker is designed to automate mundane, repetitive duties, releasing up human staff to give attention to extra strategic and invaluable work. We do that by way of Ema’s progressive agentic AI system, which may carry out a variety of complicated duties with a set 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?
During the last twenty years, I’ve labored at iconic corporations 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 cell adverts 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 how one can 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 techniques, targeted on privateness and security – Google’s Belief Graph. His experience, significantly, is a driving drive 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 should you had a Michelin Star Chef in-house who might prepare dinner something you requested for. You is likely to be within the temper for French at this time, Italian tomorrow and Indian the day after. However no matter your temper or the delicacies you need, that chef can recreate the dish of your desires. That’s what Ema can do. It might 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 various 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 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 techniques like Ema tackle these shortcomings by providing a extra tailor-made and dynamic method. In contrast to static LLMs, our agentic AI techniques can:
- Adapt to enterprise-specific knowledge and workflows
- Leverage a number of LLMs based mostly 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 be taught from real-time enterprise knowledge
- Execute complicated, multi-step duties autonomously
We guarantee seamless integration from these various sources by utilizing Ema’s proprietary 2T+ parameter combination of specialists mannequin: EmaFusionTM. EmaFusionTM combines 100+ public LLMs and lots of area particular customized fashions to maximise accuracy on the lowest attainable price for vast number of duties within the enterprise, maximizing the return on funding. Plus, with this novel method, Ema is future-proof; we’re continuously including new fashions to stop overreliance on one know-how stack, taking this danger away from our enterprise prospects.
Are you able to clarify how the Generative Workflow Engine works and what benefits it presents 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, reminiscent of 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 knowledge sources and may take actions throughout instruments to carry out successfully in numerous enterprise roles.
Ema is utilized in numerous domains from customer support to authorized to insurance coverage. Which industries do you see the best potential for progress with Ema, and why?
We see potential throughout industries and capabilities as most enterprises have lower than 30% automation in processes and use greater than 200 software program functions 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 aspects (supply).
These points are exacerbated in regulated industries like healthcare, monetary providers, insurance coverage the place a lot of the final a long time technical automations haven’t occurred because the 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 a whole lot of demand from prospects in these industries to leverage Generative AI and know-how 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 personal knowledge. Ema is constructed with belief at its core, compliant with main worldwide requirements reminiscent of SOC 2, ISO 27001, HIPAA, GDPR, NIST AI RMF, NIST CSF, NIST 800-171 To make sure enterprise knowledge stays personal, 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 circumstances, lowering prospects’ probability of IP liabilities. Ema additionally by no means trains fashions on one buyer’s knowledge to learn different prospects.
Ema additionally presents versatile deployment choices together with on-premises deployment capabilities for a number of cloud techniques, enabling enterprises to maintain their knowledge inside their very own trusted environments.
How straightforward is it for a brand new firm to get began with Ema, and what does the standard onboarding course of appear to be?
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 will wonderful tune Persona conduct with conversational directions, use pre-built connectors to combine with their apps and knowledge sources, and optionally plug in any personal customized fashions skilled 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 reminiscent of Envoy World, TrueLayer, Moneyview, and in every of those roles Ema is already acting at or above human efficiency.
Ema has attracted important funding from high-profile backers. What do you imagine has been the important thing to gaining such sturdy investor confidence?
We imagine buyers 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 workforce are specialists in AI and have the required technical data and ability units. We even have a robust observe document 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 selection 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 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 give attention to essentially the most strategic and highest-value initiatives 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 thrives, and productiveness skyrockets.
Thanks for the nice interview, readers who want to be taught extra ought to go to Ema.
