Conversational AI company
Conversational AI development services
Build intelligent conversations. At scale. With care.
What is
Conversational AI?
Conversational AI is a field within artificial intelligence (AI) that enables machines to understand, process, and respond to human language in a natural and engaging manner.
By mimicking human conversation, сonversational AI can assist customers through chatbots, voice assistants, and other interactive interfaces, providing a seamless and efficient user experience.
Why choose Devico for
conversational AI
development services?
High retention rate
96%
We go beyond the 80% industry norm with reliable, expert support.
Wide expert network
3000
Access to over 3000 engineers and AI experts.
Proven track record
500,000
Over 500,000 man-days successfully delivered.
Support
24/7
Highly experienced management team available around the clock.
Scale up with AI
Transform your business with conversational AI-powered solutions
How does it work?
01
Start with the right data
No shortcuts. Just the right signals from the right sources.
02
Make it clean
Noise out. Structure in. Data ready to learn.
03
Teach the machine
We train models to do more than respond – they understand.
04
Test it like it matters
Accuracy isn’t enough. It has to be right when it counts.
05
Launch where it lives
Real-world ready. Deployed where it makes a difference.
06
Keep it sharp
We don’t set and forget. We monitor, adapt, and evolve.
How businesses are using
Conversational AI
From enhancing customer engagement to automating support tasks, Conversational AI is transforming various industries and allowing them to scale without adding cost or compromising on service promises.
Healthcare
Conversational AI can assist patients with scheduling appointments, providing medical information, and offering mental health support. It significantly improves patient engagement and accessibility to healthcare services.
Use cases:
- Patient triage and symptom checking.
- Appointment scheduling and reminders.
- Mental health support through chatbots.
- Providing medication information and adherence reminders.
Conversational AI can assist patients with scheduling appointments, providing medical information, and offering mental health support. It significantly improves patient engagement and accessibility to healthcare services.
Use cases:
- Patient triage and symptom checking.
- Appointment scheduling and reminders.
- Mental health support through chatbots.
- Providing medication information and adherence reminders.
Financial institutions use Conversational AI to provide customer support, assist with transactions, and offer personalised financial advice. This technology helps in improving customer experience and operational efficiency.
Use cases:
- Customer service through virtual assistants.
- Automated handling of common banking transactions.
- Personalised financial advice and planning.
- Fraud detection and alerts through conversational interfaces.
Retailers leverage Conversational AI for customer support, personalised shopping experiences, and handling inquiries about products and services. This technology enhances customer engagement and drives sales.
Use cases:
- Virtual shopping assistants for product recommendations.
- Handling customer inquiries and support requests.
- Order tracking and status updates.
- Personalised marketing and promotions.
In manufacturing, Conversational AI assists with internal communication, troubleshooting equipment issues, and providing training resources. It ensures efficient operations and improved worker productivity.
Use cases:
- Real-time support for equipment troubleshooting.
- Automated internal helpdesk for employee queries.
- Providing training and safety information.
- Streamlining communication across teams.
No need to explain twice
97% of executives acknowledged that Conversational AI positively influenced user contentment
The Core Capabilities of
Conversational AI
Natural Language Processing
Helps AI understand what people really mean – not just what they say.
Practical Use cases:
01
Parsing customer queries to provide relevant answers.
02
Translating languages in real-time for global support.
03
Extracting key information from conversations for analysis.
04
Enabling multi-turn conversations for complex interactions.
Speech Recognition
Turns spoken words into text so your system can listen and respond.
Practical Use cases:
01
Transcribing customer calls for analysis.
02
Enabling voice commands in mobile applications.
03
Assisting with dictation and note-taking.
04
Enhancing accessibility for visually impaired users.
Text-to-Speech
Gives your AI a voice – so it can talk back naturally.
Practical Use cases:
01
Reading out information to users in a conversational manner.
02
Providing verbal assistance in navigation systems.
03
Offering auditory alerts and notifications.
04
Enhancing customer service with voice responses.
Dialog Management
Keeps the conversation flowing and makes sure every reply makes sense.
Practical Use cases:
01
Handling multi-turn conversations smoothly.
02
Maintaining context across different interactions.
03
Escalating to human agents when necessary.
04
Personalising conversations based on user history.
Advanced Conversational AI Techniques
The table below dives deeper into advanced Conversational AI techniques. These techniques require significant computational resources and expertise for implementation.
Criteria
Transformer Models
Generative Models
Transfer Learning
Definition
Models that use attention mechanisms to understand context and improve language understanding.
Models that generate human-like text based on input data.
tilising a pre-trained language model on a new, related problem.
Goal
Improve understanding and response accuracy by focusing on context.
Create coherent and contextually appropriate responses.
Leverage existing models to reduce training time and improve performance on new tasks.
Algorithms
Attention layers, encoder-decoder architectures.
GPT-3, BERT.
Fine-tuning pre-trained models, domain adaptation.
Data Requirement
Requires large amounts of conversational data.
Requires substantial data to generate meaningful text.
Requires less data than training a model from scratch, using pre-trained models.
Advantages
High accuracy in understanding context, ability to manage long conversations.
Capable of generating high-quality, human-like text.
Significantly reduces training time and resources, improves performance with less data.
Applications
Customer support chatbots, virtual assistants, automated transcription services.
Content creation, automated report generation, conversational agents.
Custom chatbots, virtual assistants, sentiment analysis.
Techniques
Self-attention, transformer networks, BERT.
Generative pre-trained transformers (GPT-3), fine-tuning on specific tasks.
Model fine-tuning, transfer learning architectures like GPT, BERT.
Get in touch
Drop us a line about your project and we will contact you within a business day
Our locations
New York
521 Fifth Ave, NY 10175
+1 805 491 9331London
9 Brighton Terrace, SW9 8DJ
+44 1922 214429Warsaw
Towarowa 28, 00-847
info@devico.ioLviv
Uhorska str. 14, 79034
info@devico.ioQuestions & answers
How can Conversational AI development services improve our current user support?
They help scale your support by automating answers to repetitive questions, handling peak loads, and giving your human agents space to focus on complex cases.
Can we trust a bot to represent our brand in conversations?
Yes – if it’s well-designed. A good Conversational AI development company will match your tone, context, and business logic to create natural, brand-aligned experiences.
Are conversational bots only useful for customer service?
No. Conversational AI can help in sales, HR, internal IT, healthcare, onboarding – anywhere communication happens repeatedly.