CRM-Agnostic AI For Customer Calls

Missed calls cost more than you think, especially when leads come in after hours or demand spikes without warning. From the Enterprise Connect show floor, we sit down with https://www.girikon.com and their product and innovation leaders to unpack how AI-first customer engagement is changing the way contact centers and sales teams respond in real time.

We talk through Girikon’s path from a decade of CRM onboarding and consulting into Girikon AI, including Girik Connect, a unified customer engagement platform that brings telephony, two-way messaging, and chat under one roof. The big promise is practical: stay CRM-agnostic so teams can keep Salesforce, HubSpot, Dynamics, or ServiceNow as the system of record while still connecting every conversation across channels. We explore what it looks like to deploy AI voice agents, AI message agents, and AI chat agents as the first touchpoint, so inbound callers get help fast and sales gets qualified opportunities instead of a messy backlog.

Then we get specific about enterprise realities: legacy integrations, multiple platforms, and the need to map conversation history back into the CRM with actionable insights. Think call takeaways, meeting notes, next steps, lead scoring signals, and case trends that reveal the true root cause behind hundreds of support tickets. We also dig into rollout timelines, native integrations, and open APIs, plus the hard parts of making LLMs work on real calls with noise, accents, multilingual speakers, and the risk of hallucinations.

If you care about AI customer experience, contact center automation, CRM integration, and faster speed-to-lead, this one is for you. Subscribe, share with your team, and leave a review with the AI use case you want to automate next.

Transcript

Live From Enterprise Connect

SPEAKER_01 0:00

And it's heaven here at Enterprise Connect, and we're talking to the innovators here on the show floor at Tiracon. Uh Alankar, how are you? Great. I'm doing good, uh, Ivan. Um great to be here with you and be part of this podcast. Yeah, absolutely. And Yash, how are you?

SPEAKER_00 0:16

Doing wonderful. Are you?

Girikon Mission And Background

SPEAKER_01 0:18

Doing great. Uh, it's you know, day one here. Um maybe introduce yourself, your background, a little bit about your mission at GiraCon.

SPEAKER_00 0:27

All right, so uh my name is Yesh Raj. I'm the Vice President for Product and Innovation at GiriCon. Uh, we are an AI first company. We enable businesses with uh AI-powered unified customer engagement platform that that improvises the business communication or uh vision and mission. It's it's more about enabling businesses to streamline their communication processes, uh, being CRM agnostic so that they don't have to change their tech stacks and making sure that they uh leverage the best of the AI from our tools.

SPEAKER_01 0:56

Well, it's an important mission. And Alankar, give us a little bit about the history of the genesis of the company um and your current offering. You know, what's the value add that you provide to the industry today? Sure.

Solving After-Hours Lead Overflow

SPEAKER_02 1:08

So uh GaryCon um as a business, we have been in business for um last uh more than 10 years now. We we were primarily a services company providing um CRM onboarding and consulting for many of our customers uh on Salesforce, HubSpot, Dynamics, all of these. Uh we basically now have another offering uh system, GaryCon AI, which is where we have our telephony solution as a product. Um it is on App Exchange, and we also have the cloud version, which is available to be easily integrated with all the different um CRM systems that you have. And with uh within um like you know, as part of GiriCon AI, we our flagship product is Gric Connect, which is essentially a customer engagement uh solution, uh unified customer engagement solution, which provides customers to be able to leverage the telephony, messaging, and chat capabilities. Um these are we we have our AI-powered solution, which provides AI voice agents, uh, AI message agents, and then AI chat agents. So you would a customer would be able to create all these different agents to help in the automation of a lot of the customer communication, customer engagement requirements that they have.

SPEAKER_01 2:22

Well, it's a wonderful vision. What are some of the challenges customers have in bringing that all together today in terms of messaging, in terms of you know uh the modalities, voice, text, even video, now RCS. Yep. Uh how do you over how do you help them overcome those challenges?

Unifying Channels With CRM Insights

SPEAKER_02 2:39

Uh great, great um uh question there. And in fact, we were talking to a customer um today, and one of their um concerns is that during um off office time, um, they are not able to uh handle the inbound leads that are. Overwhelming, yeah. Yeah, and and and especially they are in a business where the demand is quite um like no, it could peak at certain times and it could be lull. And our solution provides them that ability to be able to easily meet those kind of requirements. We don't have to necessarily have somebody available 24 by 7 to feel those calls from uh prospects or leads. And uh then our agents will be able to take that and then convert it into required opportunities which um which the sales team can then reach out to and all. So we we provide that ability for our customers to feel that first touch point with the with any prospects, or for that, for example, if there is any issues uh that our customer facing. So from from just doing that uh case management also, that first touch point, our agents can provide that. And then that can be plugged with not only call, messaging, two-way messaging, uh chat, and all. So you provide that um solution to uh to the customer too.

SPEAKER_01 3:56

Fantastic. And jump ball, you you or or Yash could address this one. But these enterprises and contact centers are very complex environments. Correct. Lots of legacy integrations, multiple platforms, multiple contact centers, um, different kinds of messaging modalities and standards. How do you bring all that to how do you integrate into all of that?

Fast Rollouts With Native Integrations

SPEAKER_00 4:14

That that is where we come in picture, right? So uh the kind of platform that we have built, it is CRM agnostic, as I've stated earlier as well, right? So when we say CRM agnostic, every enterprise, as you rightly said, uses different tools, different uh CRMs, tech stack, right? Making sure that all their data stays in one ecosystem is very important today because conversations across these platforms are different. What we are doing is we are bridging that gap, okay, and we with Gric Connect as GIRICON, we are bringing all these uh integrations in one place, right? So that you can easily connect with that specific CRM, making sure that all your conversations are read well, okay, because every conversation carries a history and important details about it, and they are mapped into that specific CRM with actionable insights. And when I say actionable insights, suppose we have a call today, okay. With this call, what are the details that we are taking out? Your takeaways, your minutes of meetings, okay, what are the next steps that I can bring in? Okay, all this will be mapped right into your CRM. With that, your business owners have a visibility of the conversation where they are heading towards the business. So if they are working for a sales team, okay, I need to uh understand what where my sales team is hitting today, how many apportion is they have closed out of hundred calls that they have taken. I can give that insights rightly inside the CRM, okay? Making sure that out of hundred calls, 10 calls were positive, okay, which are going to close within the next two weeks. That are the hot leads for me that I can clearly focus on. Same with case management, right? When it comes to contact centers, we get hundreds of cases every day, correct? But with these hundreds of cases, what are the main issues that customers are facing? That is really, really important. Instead of just keeping my customer support team occupied and responding to responding to those emails or those conversations or those calls, right? What we do here is we bring in insights and information for you from those conversations, okay, and we find out that one point where uh issue is fixed within a bug. Maybe if it's a product issue, we can just look after that product issue instead of addressing that separately for every customer. And we can just email the customer, hey, we identified your issues. Out of these hundred cases, we know that 70 of the customers that are facing a similar challenge, we will fix that in a product itself as a business owner, right? Very cool. So you you handle that more efficiently, you handle that with actionable insights, and you can notify your customers in real time. Very powerful.

SPEAKER_01 6:36

And uh, I guess next question is um, you know, implementing new systems is difficult in an enterprise. It's like you know, you're changing the engine of a plane while it's in flight. How do you think about integrating? How quickly can some of these services be rolled out on your platform? Are you talking weeks, months, uh could it be days to bring all the data and the channels together in a unified way?

SPEAKER_02 7:02

Yeah, so uh what we have done as a platform is we already have built in integration with some of the major providers already, like Salesforce, HubSpot, ServiceNow and all. And those can be done in weeks. Like the integration is already available. For us, it's uh uh it's important to understand what the business use case our our customers trying to solve for, and then configure the system, uh, the platform, and then the integration accordingly. Um and also we have open API. So if there are if there are needs where you need some custom integration to be done, we have team members who would be able to easily solve for those as well. So we like and we understand, especially with AI and all, now the expectation is we really need to move fast. We can't take days and days and months to just implement a solution. So uh we that's that's how we have designed the solution. We have already built-in native integrations with many of these uh platforms, but then also we have open APIs which can be easily called, and uh our our customers can easily integrate with their tech stack.

Practical AI Use Cases By Industry

SPEAKER_01 8:04

Fantastic. You mentioned AI, and of course, AI has turned everything upside down in our space. CX, it's reinventing the entire CX space. What are the biggest opportunities for leveraging LLMs and AI tools and and even um voice bots from your perspective? Are do you have any unique uh use cases uh from your side?

SPEAKER_00 8:26

Definitely. There are multiple use cases that we come across. It's more about learning new business opportunities as I see and that are like industry specific. You talk about healthcare today, right? Patient care is something which is uh a biggest challenge. You have to have uh people or care executives available 247. Look at the opportunity there, wherein the AI can come and picture qualify intakes for you, capture patient details, address their emergency needs, and transfer those calls whenever it is needed, right? With a transfer context that we specialize in. Financial services, one of the most or the biggest industry that uh is there in the customer success space now, wherein uh your insurance agents, your policies of insurances, uh your status updates, application updates are being captured rightly by the uh AI agents, and they are providing the real-time information as well. Lead qualification across industries, be it education, be it uh financial services, real estate, uh communicating and uh with with the uh new leads that you receive in real time. Okay, because you getting a lead via Zillow or any other third-party platform, okay, reaching out to that lead in real time is something which is a task. Today, AI agents are doing the job, which is capturing hot leads for you, making sure your sales teams are working on the hot opportunities that they should be working on to. Instead of just dialing randomly, making hundreds of calls a day and not getting any outputs, right? They can't that that can that job can be done by the agents, right? And with insightful information that is available to you in real time.

Roadmap Plus Real-World AI Limits

SPEAKER_01 9:59

Wow, so exciting. Uh speaking of which, what are you most excited about over the next weeks and months? What any particular features or functionality or new new uh versions coming up? What's on your radar as far as um a platform?

SPEAKER_02 10:13

Yeah. No, I and I think just like you know, picking up from your previous question also, AI is moving fast. And we have these errums which are coming with a lot of new uh with new models every other week, month, right? So for us as a solution provider, we are here to be able to then use that and really solve the business, real business use cases for our customers. So for us, it's important that we are looking at what's coming and then accordingly uh enhancing the platform to be able to solve those use cases. And I think that's where, like, you know, while um you you have these LMs providing you some of these solutions, for us it's important that how do we really make it work for our customers, right? Um and when you start actually solving for it, that's when you can get into the nuances. All right, I am let's say if you talk about voice, right? Um somebody's taking a call in a crowded space, or you cancel the noise that is there, right? Different accent, um, multilingual. So all those are different use cases which actually then test the capability of AI. And that's where we come in, to be able to really use all these uh developments that are happening in the LLM space to then then actually solve for the customer. Because until those those things are not solved, it doesn't work. Like there will be a lot of hallucinations, you'll not get the right answers, you will get some different, and and that's where we are here to ensure that our solution is taking those real real-time use cases and then solving for our customers' need. And and and many of the customers that we have talked to, we see that they they want to adapt AI, but those are the concerns that they have. And as we work with them, they get they are getting more and more comfortable, and then they are really using it now to to really serve serve their end customers.

SPEAKER_01 12:00

Well, it's a mic drop moment if I ever heard one. So thank you. Congratulations, and I know you have a very deep technical bench. Well done. And uh here's to uplifting the CX and contact center industry. Definitely. Thanks very much.

SPEAKER_02 12:12

Yeah, it was really nice talking to you, Evan.

SPEAKER_01 12:13

Likewise, take care. Thank you. Thank you.