In 2026, Interactive Media marks an important milestone: 30 years of activity in the field of contact center automation and customer interaction technologies. Founded in Italy in 1996, the company has gone through all the main evolutionary phases of customer service, contributing concretely to the development of increasingly advanced, reliable, and user-focused solutions.

From the first tone-based IVR systems to today’s conversational virtual agents powered by Artificial Intelligence and generative AI, Interactive Media has built a path of continuous innovation, deep technological expertise, and successful projects for large public and private organizations.

This milestone celebrates the company’s history, vision, technologies, and the value Interactive Media brings to the market today, while looking forward to the future of intelligent automation.

Origins: Voice Automation in the 1990s

When Interactive Media was founded in 1996, the concept of digital customer experience was still far from today’s maturity. Contact centers were handling growing call volumes and beginning to adopt IVR (Interactive Voice Response) systems based on DTMF, i.e., through telephone keypad input.

In this context, Interactive Media stood out as a pioneering company in voice automation solutions, working from the start with large and complex clients such as telecom operators and national public entities. The ability to ensure stability, service continuity, and integration with existing infrastructures became one of its first distinguishing factors.

This initial phase allowed the company to acquire deep knowledge of contact center operations, a competence that would remain central in the years to come.

From Traditional IVR to Advanced Platforms

In the early 2000s, the market demanded increasingly flexible and high-performing solutions. Interactive Media invested in developing proprietary media servers and application servers designed to handle high traffic volumes.

At the same time, integration with external systems—CRMs, authentication systems, databases, and third-party contact center platforms—became increasingly important. Interactive Media responded by building robust connectors and integration architectures capable of adapting to complex and often heterogeneous technological contexts.

This approach allowed client companies to introduce automation without disrupting their IT ecosystems, reducing risks, costs, and implementation time.

The Breakthrough of Natural Language and Artificial Intelligence

From 2010 onward, customer service underwent a radical transformation thanks to advances in voice recognition, natural language understanding, and Artificial Intelligence.

Interactive Media embraced this evolution and became one of the first players to bring natural dialogue into contact centers. Interaction was no longer guided by rigid menus but became a smooth conversation in which users could freely express their needs.

The first intelligent voicebots were born, capable of:

• understanding user intent
• managing complex dialogues
• accessing company information in real time
• adapting the conversational flow to context

This evolution significantly improved the customer experience and allowed companies to automate increasingly complex processes.

OMNIA and Conversational Virtual Agents

Today, Interactive Media’s core offering is represented by conversational virtual agents, with particular excellence in the voice channel. The OMNIA platform was created to provide omnichannel AI, capable of operating on phone, chat (web or social media), and other channels and devices.

OMNIA virtual agents are designed to work alongside human operators or to replace them in repetitive, high-volume processes, ensuring:

• 24/7 service continuity
• reduced waiting times
• more consistent responses
• significant operational cost reduction

In case of escalation to a human operator, the system transfers the conversation context, so the customer doesn’t have to repeat information.

MIND: The Artificial Intelligence Engine

At the heart of Interactive Media’s conversational AI solutions is MIND (Multimodal Interactions through Natural Dialog). MIND is the technological core of OMNIA, the intelligent engine that enables virtual agents to understand user intent and manage conversation flows dynamically and naturally.

Although fully integrated into OMNIA, MIND is extremely flexible: it can also be used within PhoneMyBot, where it is optional and can coexist with other textual AI engines.

PhoneMyBot: Giving Voice to Chatbots

In recent years, Interactive Media expanded its offering with PhoneMyBot, a solution that enables voice interaction within existing chatbots.

PhoneMyBot is an open platform, compatible with various textual AI engines, providing a practical response to the growing demand for voicebots integrated into cloud contact centers, particularly on Genesys Cloud CX.

With PhoneMyBot, companies can:

• reuse existing chatbots for voice channels
• accelerate implementation times
• maintain a consistent conversational experience
• easily integrate telephony, AI, and backend systems

Integration of Generative AI

The introduction of generative AI represents a new phase in the evolution of Interactive Media solutions. This technology makes conversations even more natural, contextual, and flexible.

Generative AI allows companies to:

• handle unstructured requests
• improve linguistic quality of responses
• adapt tone of voice to context
• speed up dialogue design

Interactive Media integrates these technologies in a controlled and secure way, ensuring governance, reliability, and compliance—essential for enterprise clients.

On Premises and Cloud Solutions: Maximum Flexibility

One of Interactive Media’s strengths is offering both on premises and cloud solutions, meeting the needs of highly regulated sectors such as public administration and finance.

The architectures are designed to ensure:

• high security standards
• scalability
• operational continuity
• integration with legacy systems

This flexibility allows companies to adopt conversational AI according to their technological and organizational constraints.

Global Technology Partnerships

Over the years, Interactive Media has built strong technology partnerships with market leaders such as Google, Microsoft, and Genesys.

The company is a Google Cloud ISV Partner, operates on Microsoft Azure architectures, and is present in Genesys AppFoundry with PhoneMyBot, enabling intelligent voice channels integrated with Genesys Cloud CX. These collaborations allow for reliable, scalable platforms aligned with international standards.

Hundreds of Millions of Conversations Each Year

Today, Interactive Media handles hundreds of millions of conversations annually, in multiple languages and across various channels. This demonstrates the reliability of its solutions and the robustness of its technological infrastructure.

With headquarters in Italy and offices in the United States and Brazil, the company supports clients internationally while maintaining a highly specialized, quality-focused approach.

Mission: Making Customer Service More Human Through Technology

Interactive Media’s mission is clear: to use technology to make customer service more efficient, accessible, and enjoyable for both companies and end users.

Over the past thirty years, contact center automation has been not just a technological evolution, but a paradigm shift in business models. Interactive Media has guided organizations through this transformation, helping them rethink customer service as a strategic lever rather than a mere cost center.

With conversational virtual agents, companies can ensure service continuity, drastically reduce operating costs, and improve brand perception. Automation allows large volumes of interactions to be handled without compromising quality, turning the contact center into a value hub.

Automation does not mean dehumanization—it means freeing resources, reducing friction, and creating better experiences.

Voicebots and Rediscovering Voice in Customer Service

While the trend has often been seen as replacing voice with apps and digital channels, field experience proves the opposite: voice remains a preferred channel, especially for complex or urgent issues.

Interactive Media has built its positioning on this insight, investing in advanced voicebots that offer natural, fluid, and reliable interaction. Voicebots do more than provide predefined answers—they understand context, handle exceptions, and interact increasingly like a human operator.

User Experience as a Competitive Factor

Today, customer experience is a key differentiator. Reduced waiting times, immediate responses, and channel consistency are critical for customer satisfaction.

Interactive Media solutions are designed with the end-user experience in mind. Every conversational flow is built to be simple, intuitive, and goal-oriented, minimizing frustration often associated with traditional automated systems.

Integration with Legacy Systems and Complex Environments

A critical aspect of automation projects is integration with existing systems. Many large organizations operate on layered infrastructures, often including legacy technologies.

Interactive Media has made integration a key strength, developing solutions that communicate with CRMs, billing systems, corporate databases, and contact center platforms. This ensures existing investments are preserved and conversational AI is introduced gradually and sustainably.

Application Sectors

Interactive Media solutions are successfully used in:

• Telecommunications
• Public administration
• Financial and banking services
• Mobility and transportation

In these contexts, conversational AI has proven to significantly improve operational efficiency and end-user satisfaction.

Automation in Public Administration: Efficiency and Accessibility

In public administration, automated customer service is even more strategic. Entities must provide services to millions of citizens, often with limited resources.

Interactive Media solutions offer always-available services, reduce phone queues, and improve accessibility, even for less digitally savvy users. Using voice as a natural interface is a key inclusion factor.

Security, Reliability, and Data Governance

In AI-driven customer service, security, reliability, and governance are essential. Interactive Media designs solutions to operate in enterprise contexts where data protection and operational continuity are critical.

Architectures ensure high security standards, access control, and interaction traceability, meeting the needs of highly regulated sectors like finance and government.

An Evolving Market and Future Challenges

The conversational AI market is rapidly evolving and increasingly competitive. In this context, Interactive Media stands out for its robust solutions and deep expertise in telephony automation.

Every solution is backed by strong R&D investment. A dedicated team continually evolves the platforms, improving scalability, reliability, and the cognitive abilities of virtual agents.

With over thirty years of experience, the company can handle complex projects pragmatically, based on real cases and measurable results, avoiding unrealistic promises.

Future challenges include integrating new technologies, maintaining high-quality standards, and supporting clients in continuous transformation.

30 Years of Innovation, Looking to the Future

Interactive Media’s 30th anniversary is not only a celebration of the past but also a reflection on the future of intelligent automation.

With a history dating back to 1996, global technology partnerships, and a clear vision of customer service evolution, Interactive Media remains a strategic partner for companies seeking innovation, professionalism, expertise, and sustainability.

Many deployed chatbots are far from holding real conversations. But they too can be enabled for fluent dialog. This is how we do it.

When you consider chatbots these days you think of ChatGPT, Google Bard, Bing Chat, etc. These are all based on Large Language Models (LLM) and are able to answer pretty much any question that users may ask. But in fact, there are thousands of deployed chatbot that help users with customer service issues every day, which are way more limited. Many chatbots in use today have simple interfaces with predefined questions that users can select by typing keywords or clicking on buttons. They work, sometimes they work well, depending on the domain and the type of business they serve. But there is no question that using these chatbots for voice interactions would result in a bad customer experience. That is, unless we at Interactive Media intervene.

In this article I will describe how to enable even these chatbots for voice, with excellent customer experience.

Type of chatbots

According to a blog post by IBM, there are four categories of chatbots:

1. Menu or button-based chatbots. These are the simplest chatbots, very much deployed on web pages, that guide the user through explicit choices. They are equivalent to the traditional tone based IVR for voice and can work well if the domain is simple and the choices are clear. Obviously, if the user needs something that is not included in the menu, they can’t help and should refer the customer to a human representative.

2. Rules- and keywords-based chatbots. These chatbots let the customer ask questions in somewhat free format, then match keywords in the question with their knowledge base and present text that contains those words. They are in essence interactive FAQ reading tools. The problem here is that if the question is complex, these chatbot can’t answer it and should forward the interaction to a human.

3. AI-powered chatbots. These chatbots have Natural Language Understanding (NLU) and Natural Language Processing (NLP) capabilities and can handle dialogs with multiple exchanges with users. They are based on AI engines acting on a knowledge base that is tailored for the specific domain they are serving. This means that, users can ask any question about information in the domain, and the chatbot will understand the question and answer according to its knowledge. Sometimes the chatbot will ask a clarification question if the user’s initial question is ambiguous. However, if the user asks something outside the chatbot specific knowledge base, the chatbot will not be able to answer.

4. LLM-based, generative AI chatbots. Well, these chatbots have been all the rage in the past year or so. They are fluent and can answer any question, since their knowledge base is enormous, they can also create new answers by putting together information and text in a statistical way. They are the future, and the high-end present, of customer service, as one of their applications. But there are many others…

If you read about chatbots in magazines and specialized websites, you’ll find 90% of the articles about the 4th type, maybe still 10% about the 3rd type, and nothing about #1 and #2. But many #1 and #2 chatbots are still serving customers – and will for years to come: they are paid for, and 3rd and 4th type chatbot applications for customer service are expensive.

Where simple chatbots can do the job well

Sometimes you don’t need sophisticated AI chatbots to serve your customers well. If the customer service domain is simple, the questions asked are for the most part always the same, and you want users to feel at ease with clicking buttons or following menus, a simple, Type 1 chatbot will do just fine.

For example, banks have a limited number of services that they can perform using chatbots. For this reason, often the UI consists of a series of buttons and menus where the user selects one item and continues to the desired service.

Another example may be purchasing a train ticket. You want the user to specify the date of the trip, the origin station, the destination, and the class of travel. Easy peasy. A chatbot with web widgets and keywords matching for cities will do the job.

How to enable dialogs and voice with simple chatbots (without excessive costs)

Even a simple chatbot like a type 1 has access to a valuable knowledge base that would be great to access by voice. And indeed, Interactive Media offers a service to add the voice channels to chatbots easily and conveniently, called PhoneMyBot. But a type 1 chatbot needs precise inputs from users which are not easily translatable into a voice conversation. Here we can use an add-on to PhoneMyBot, implemented using Interactive Media’s conversational AI platform, MIND. In essence, we add a very simple type 3 application in front of the main type 1 chatbot, able to figure out the intent of the call through a natural language dialog.

Once the intent of the call is determined, if it’s covered by the type 1 chatbot, MIND crafts the question in the format that the type 1 chatbot expects and sends it forward. PhoneMyBot will then retrieve the answer from the chatbot and speak it to the user. If the intent of the call is not in the chatbot’s knowledge base, MIND can determine to send the call to a human agent instead. This works with one chatbot, or several. Sometimes companies deploy more than one specialized chatbot for different tasks and MIND acts as aggregator and selector for the most useful chatbot.

This figure shows the architecture: PhoneMyBot and MIND exchange information initially, before connecting the caller to the chatbot.

For Interactive Media, this is a simple call steering application. We have developed many of these over the years and we can implement one fast and with contained costs. It’s a very cons-effective solution to add the voice channel to even a simple chatbot.

We would love to put more meat on the bone and talk to you about this solution: please contact Interactive Media at contact@imnet.com  or click the button below.

ChatGPT and its siblings are all the rage in customer service chatbots. This is fascinating and terrifying. How do we take the terror out of the equation?

In the past year or so we witnessed an explosion of chatbots based on Large Language Models (LLM). The adoption of LLM technology in conversational AI is truly revolutionizing the field, with a user experience that is better by leaps and bounds than what was coming before. They hold immense promise for applications as varied as customer service, simultaneous translation, general information delivery… anything that has to do with connecting the public with data through natural language, either text- or voice-based.

But not all is bright and beautiful in AI land. There are also significant challenges. In this article I give my take on some of the most common challenges and suggest possible ways to overcome them.

Large Language Models predictability

LLMs are an enormous collection of information fragments, that the AI algorithm connects in a statistical way. In order to provide answers, the algorithm takes the most probable path connecting a certain fragment to another, starting from the question, and considering the question’s context: who is asking it, what the setting for the question is… This process does not always lead to a predictable outcome, as it always happens when statistics is involved.

For some use cases, this would not be a be an unsurmountable issue if answers from LLM chatbots vary to some degree. A conversation summary for instance can be rendered in many different ways, all pretty accurate. Or a product can be recommended by an LLM based algorithm with different words and sentences.

But there are many other applications, more related to core customer service capabilities, where precision is paramount and slip-off could be costly: anytime there are legal implications for instance, or when the chatbot is used as an initial screen for someone to get a loan. In these cases, while the potential of LLM-based algorithms is clear, the risk must be mitigated.

Large Language Models sensitivity to input changes

Language is fluid, and there are typically many ways to say the same thing. English, speakers, like all humans, rely on turn of phrases, metaphors, and synonyms to express themselves. Not everyone will use the same words to ask for the same thing, also depending on the speaker’s education, frame of mind, age, location… As George Bernard Shaw said: “England and America are two countries separated by a common language” – well, even if the language is nominally the same, if the listener is an LLM-based chatbot, the same request could take vastly different meanings depending on the words used.

As an extreme example, suppose that one speaker says: “What would it take to cover all the bases and hit it out of the ballpark?”

Another speaker says: “How can we eliminate risk and be very successful?”

In American English, a human would understand these two sentences to say the same thing. But while speaking to a chatbot the result can be very different, depending on if the chatbot catches on the metaphors.

A solution: sanitizing the input

Sending to an LLM-based chatbot always the same words for each question would solve quite a bit of the precision problem. This is impossible to do in a free domain, where users can ask virtually any question. But it is possible, even relatively easy, in a well-defined domain like a customer service one. What we propose is to front the LLM chatbot with a call steering system, which uses natural language to determine the user’s intent, possibly with a dialog made up of several exchanges. Once it determines the intent, the call steering system send the chatbot always the same worded question for that particular intent, which will have been vetted and tested to produce the best result.

Interactive Media has a long experience with conversational applications and a standard structure and process to create applications that perform call steering. So, we have created an all-in-one platform to help users interact with LLM chatbots in a customer service environment. We integrate PhoneMyBot, Interactive Media’s service to provide the voice channel to any chatbot with our call steering platform, MIND, and the LLM chatbot that is actually doing the heavy customer service part. When users call in they reach MIND, which asks them questions about what they need, possibly in more than one exchange, and classifies their answers to one of the intents available in the domain. Then it sends back the standard question for the intent, which PhoneMyBot forwards to the chatbot, receiving the answer and relaying it to the user.

This technique increases the quality and precision of LLM chatbots, making them more suitable for work in a customer service environment.

We would love to put more meat on the bone and talk to you about this solution: please contact Interactive Media at info@imnet.com or click the button below.

Last week I watched a webinar and demo by a company providing tools and solutions for conversational customer service. Interactive Media, where I work, is in the same sector and I wanted to scoop out a competitor, see what they have and how they are presenting their solutions to the market. Everyone does this of course; I don’t feel bad about it in the slightest.

This company was presenting with great emphasis a solution that allows a caller to synchronize a voice call (on a smartphone) to a visual IVR component. In essence, when users call, they are offered the option to receive a text message that contains a link to a personalized web application. The web app provides information about what the call is about, and you can navigate it by clicking on the pages, or by voice.

In the demo, this provides a great experience: all the information regarding the case is at the user’s fingertips, and it’s much easier to insert additional data. For instance, think about how hard it is to dictate an email address to an agent (let alone a virtual assistant!). With this type of visual IVR, the user can simply type it into a box, a much more efficient and error-free process.

This particular solution is not simple: you have to use conversational AI to understand what the caller says, being able to identify the intent and navigate precisely by voice, populate the web pages to service the intent on the fly, create and send the link by text message, and, most difficult of all, synchronize the voice and web parts of the session. Well done!

But seeing this demo left me rather surprised: you see, I was doing exactly the same demo with Interactive Media software 5 years ago (and I have the videos to prove it). This made me realize two things. One is that the Interactive Media people and technology are kick-ass, well ahead of most competition. But the other, considering that I was not able to sell this solution, is that sometimes focusing on increasingly sophisticated, “frictionless” services does not pay.

That demo is fantastic, but how many similar applications have you seen in real life? And, based on your real-life experience, how often would you need something similar? In essence, it seems to me that we as an industry are targeting increasingly complex software solutions to an ever-decreasing number of users.

The vast majority of users hope to never have to contact customer service. But when they do it is often for a simple question, one that does not in general need this type of infrastructure. Normally, users can search the company web site, chat with an agent or a chatbot, call in. A good percentage of people calling in does so because they are not comfortable with other channels, either because they are on the move and voice is the best way to interact, or because not everyone is familiar with web technology. Again, as an industry, we tech people tend to project our own experience onto everyone; folks, this is not the entire world!

For people who call in only with voice, there is PhoneMyBot, the Interactive Media service to provide voice channels to chatbots with a no-code, ready to roll approach. Companies that have deployed chatbots but have no conversational AI on the voice channels can use PhoneMyBot to enable telephone conversations with their existing self-service app. Conversational AI vendors who only support textual and web channel can use PhoneMyBot to offer voice channels to their customers. PhoneMyBot targets simpler self-service voice solutions for the vast majority of users.

But if you really need a synchronized voice and Visual IVR application for flashy service to your most tech-savvy customers, why don’t you also call Interactive Media? After all, we have a 5-year advantage.

Please go ahead and try PhoneMyBot for free: contact Interactive Media at info@imnet.com or click the button below.

Talking with ChatGPT over the phone is cool. But we can also make it useful.

In the past few months tech people worldwide have been talking almost exclusively about Open AI’s ChatGPT. It’s the first large language model chatbot to make a splash, and what a splash! It landed with the energy of the Chicxulub asteroid – the one that killed the dinosaurs 65 million-odd years ago in the Yucatan sea. That asteroid generated a mile-high tsunami, almost as high as ChatGPT’s. One should go slow with the metaphors though: are ChatGPT and its peers going t kill …[gasp]… us? As an incorrigible optimist and I don’t think so, but the jury is out according to much of the press.

But as we all know, even if a device could cause the end of the world as we know it, if it’s new and shiny people will use it. So, after using ChatGPT to write poems about pickleball or essays on Tibetan literature, the tech community is trying to understand what it can do for real business.

For instance, we at Interactive Media have integrated ChatGPT with PhoneMyBot, our service to provide voice channels to chatbots with a no-code, ready to roll approach. Through PhoneMyBot it is now possible to make a phone call to ChatGPT, ask questions and listen to its answers. This is still only a demo, but in the process we have developed some useful ideas on whether and how ChatGPT may work for what we do normally, which is providing tools to companies to service their customers.

Let’s say it immediately: without personalization, ChatGPT is not sufficient to implement a customer service voicebot. The domain is too wide: it is literally the whole Internet. This means that ChatGPT cannot use its normal language model to answer pointed questions on – say – your bank balance today.

To be sure, in customer service there is sometimes a need for general-purpose conversation. In our experience, users sometimes go out on a tangent and ask bots all sorts of questions. For instance: where do you live? how old are you? can I see you? how much are you paid?… ChatGPT certainly has good answers for all these questions, and it would be useful in side conversations. ChatGPT is also language-independent: in essence it can tell what language a user is speaking and answer in the same language. This is a stunning capability and it makes it so much easier to use ChatGPT.

However, it is possible to “fine-tune” ChatGPT for specific domains, adding dozens, hundreds or thousands of examples of specialized prompt-completion pairs that define a separate domain, identified by its own name and id. This domain goes to augment the general-purpose model and allows the chatbot to answer pointed questions. At Interactive Media, we are experimenting with fine-tuning one of the available general purposes models and we can certify that it works: if ChatGPT has the necessary information, not only it answers to precise questions about the specific domain effectively, but also in a pleasant and precise way.

Often, however, customers’ questions may be ambiguous and hard to characterize. In this case ChatGPT can’t be allowed to answer immediately as what it says would be vague or incorrect. But Interactive Media’s conversational AI platform, MIND, placed in front of ChatGPT, can easily be configured to deal with these cases. MIND can identify the real intent of the caller through an initial dialog, and only after that forward the “real” question to ChatGPT. This makes a huge difference in the conversation outcome.

There’s another snag though, because to be useful you also need to access actual data related to the people’s requests. ChatGPT of course does not perform the appropriate database queries into company databases or CRMs. To counter this at Interactive Media we have developed a generalized method to access database data and to insert this data into ChatGPT’s answers. Of course, depending on the data this has to be done on a case-by=case basis, so call us to discuss!

Please go ahead and try PhoneMyBot’s connection with ChatGPT: contact Interactive Media at info@imnet.com or click the button below.