Your customer writes to the chat at 11 p.m. to ask where their order is. Within seconds, they receive not just an answer but also a personalized recommendation and a coupon for their next purchase — all handled by an AI agent without human involvement.
This is not a script-based bot but a fully-fledged digital executor that accesses databases, analyzes customer behavior, and acts based on business logic. The size of the market for such solutions is growing exponentially from $13.8 billion in 2025 to $140.8 billion in 2032. In this article, we will mention the companies that will keep you ahead.
Understanding AI Agents: What They Are and How They Work
AI agents are autonomous intelligent systems capable of understanding goals, planning actions independently, adapting to changes, and achieving results without constant human intervention.
Unlike traditional AI, which responds to individual requests (e.g., “create a report”), AI agents act proactively, break tasks down into stages, interact with external services, and make decisions in real time.
How they differ from traditional software and AI systems:
| Characteristics | Traditional AI | Agent AI |
| Focus | Single task | Targeted strategies |
| Initiative | Reactive | Proactive |
| Memory and learning | Limited | Long-term memory |
| Interaction | Passive | Active |
| Planning | Simple | Multi-step, goal-oriented |
Comparison of Traditional AI vs Agent AI
Benefits of Implementing AI Agents into Real Business Scenarios
The implementation of AI agents into business processes gives companies a powerful boost in automation, scalability, and cost reduction. These agents take over routine tasks — from handling requests to making decisions — working 24/7 without compromising quality.
AI agents provide faster data processing and decision-making, minimize human error and mistakes, and improve the customer experience through personalized and instant responses. With the ability to analyze large amounts of information in real time, AI agents help identify hidden patterns, predict user behavior, and respond quickly to market changes.
Best Ways to Implement AI Agents into Real Business
For implementation to be effective, however, it’s important to clearly define objectives and launch the solution. When properly configured, an AI agent quickly becomes not just a tool, but a full-fledged member of the business team.
Equally important is integrating the agent with key business systems — CRM, databases, API platforms — so it can operate effectively in a real environment rather than in isolation. With proper configuration and training, such agents not only enhance business operations but also become an integral part of them.
Criteria for Choosing an AI Agent Development Partner
When choosing a company to develop AI agents, it is important to consider not only technical capabilities but also the overall approach to project implementation, level of expertise, and readiness for long-term cooperation. Below are the key criteria that will help you choose a reliable and competent partner:
| Criterion | What to look for |
| Experience | Number of years in the market, completed projects with AI agents, case studies in your industry. |
| Technologies | Stacks and frameworks used (e.g., LLM, LangChain, RAG, Python, TensorFlow, etc.). |
| Expertise in custom AI agent development | Ability to create custom solutions tailored to the client’s business processes. |
| Security | Compliance with standards (GDPR, ISO), data protection, access control, secure integration. |
| Post-support and maintenance | Readiness for post-release support, team training, AI consulting, regular updates, and optimization. |
Criteria for Choosing an AI Agent Builder
Top AI Agent Development Companies in 2025: Our Selection Criteria
To identify the leading AI agent developers in 2025, we have analyzed companies based on a range of criteria. First and foremost, we evaluated their portfolio of completed projects, including both off-the-shelf solutions and custom developments. We also considered client reviews that confirmed the practical value and reliability of the collaboration.
Special attention was given to expertise in AI agent development — specifically, the ability to build intelligent agents that interact effectively with users, integrate with IT infrastructure, and solve specific business problems.
In addition, we assessed how well companies keep up with the latest trends in artificial intelligence in 2025 — from the use of LLMs and RAG-based approaches to ensuring the security and scalability of their solutions.
Top 10 AI Agent Development Companies in 2025
In 2025, the production of AI agents became a key element of digital transformation: from autonomous chatbots to complex virtual assistants. Below are the best companies that create custom AI agents, integrate generative AI, and prove the effectiveness of their implementations.
1. SCAND – Custom AI Agent Development with Enterprise Expertise
SCAND (Poland) has over 25 years of experience in software development and successfully implements projects in the field of artificial intelligence, including the creation of AI agents.
Key areas of focus:
Custom agents, voice assistants, chatbots, intelligent virtual assistants.
- Customization for industry-specific processes and integration into existing IT infrastructure
- Development approach and AI tools used:
- Agile methodologies, discovery workshops, PoC → MVP → full deployment
- OpenAI API, TensorFlow, Dialogflow, and Rasa
- RAG architectures, self-hosted or hybrid cloud-based solutions
Strengths:
- Scalable architectures
- Compliance with GDPR / ISO standards
- Deep understanding of the client’s business context
- Dedicated team model
Implementation cases:
- AI Development in Logistics
- AI-Powered Source Code Documentation
- AI Parking Management for Golf Clubs
- Smart Travel Guides Search
2. Deviniti – Enterprise-Grade Generative AI & Custom Agents
Deviniti is one of Poland’s leading AI companies with nearly 20 years of experience, specializing in secure, self-hosted AI agent development.
Key areas of focus:
Generative agents, PoC/MVP development, RAG-based solutions, fine-tuned LLMs.
- Industry focus: Banking security, legal, and financial sectors
- Development approach:
- Discovery workshops → PoC → enterprise deployment
- Self-hosted LLMs, RAG systems, multi-agent orchestration
Strengths:
- A team of ~330 AI specialists, certified with ISO standards
- Full data control, compliance with GDPR/HIPAA/SOC 2
Use case:
Credit agent for Credit Agricole: automatically handles simple requests, routes complex ones, and generates responses and PDF documents.
3. Master of Code Global – High-Complexity, End‑to‑End AI Agent Builds
Founded in 2004, Master of Code Global brings over 19 years of experience in Conversational AI, LLM-based solutions, and enterprise agent development.
What they offer:
- End-to-end AI agents: from conversational interface design to full backend integration
- Multi-channel solutions (chat/voice), reasoning agents, CRM/ERP integrations
Tools and approach:
ISO 27001 certified, proprietary LOFT framework for accelerated delivery and cost reduction.
Key advantages:
- Experience with global brands (MTV, Burberry, T-Mobile, and others)
- A team of over 250 engineers, 400+ completed projects, serving more than 1 billion users
Use cases:
Conversational interfaces with analytics and integration into large-scale enterprise systems.
4. ManoByte – Alignment‑Driven Agentic Solutions for B2B
ManoByte focuses on developing AI agents for mid-market and enterprise B2B clients, with a strong emphasis on understanding and aligning with business logic. They specialize in integrating agentic solutions directly into the client’s operational workflows.
Core areas of expertise:
- Identifying pain points in business processes
- Configuring multi-agent systems aligned with CRM and go-to-market strategy
Approach:
Process modeling + process intelligence + AI orchestration
Strengths:
- Deep integration with the client’s lifecycle and strategic objectives
- Scalable solutions that grow alongside the business
Use cases:
AI agents for sales, marketing, and customer support, enabling automated decision-making for B2B clients.
5. SoluLab – Cross‑Industry AI Agent Deployment
SoluLab specializes in AI agent solutions tailored for fintech, e-commerce, healthcare, and logistics sectors.
Primary focus:
Autonomous agents with multimodal input capabilities (text, voice, image, video), utilizing AutoGen and Vertex AI Agent Builder.
Approach:
Secure development under ISO 27001, flexible architectures, multi-agent workflows, and behavioral training of agents.
Key advantages:
- Trusted by Fortune 500 clients such as Disney and Goldman Sachs
- High technical adaptability and strong client confidence
Use cases:
Voice-enabled AI agent for e-commerce. Coordination agent for logistics operations.
6. Markovate – Conversational & Marketing AI Agents
Markovate specializes in chat-based AI agents and marketing-focused AI solutions, with a strong emphasis on personalization and customer engagement.
Focus areas:
Context-aware agents, retention marketing, and structured conversation workflows.
Approach:
UX-first design, tone-aware responses, and in-depth behavioral analytics.
Strengths:
- Ideal for eCommerce and B2C projects with high user engagement
- Tailored solutions that drive personalized interactions and loyalty
Use cases:
AI agent for personalized marketing campaigns and automated customer interactions.
7. 10Clouds – Polish Product House with AI Lab
10Clouds leverages its in-house AILab and proprietary AIConsole platform to create flexible, product-focused AI agents.
Core focus areas:
Customer support agents, sales enablement, HR automation, healthcare assistants.
Approach:
- Seamless integration of design and ML engineering
- Product-oriented agent development with rapid PoC cycles
Key advantages:
- Strong UX teams combining design and AI expertise
- Fast turnaround from concept to functioning agent
Use cases:
UX-driven virtual assistants and AI-based recommendation agents.
8. NICE – CXone Mpower Orchestrator for Customer Service Automation
NICE Ltd offers the CXone Mpower Orchestrator platform, delivering AI-driven automation for customer service, workflow orchestration, and Copilot functionalities.
What they do:
- Integrated voice and chat agents at the enterprise level
- Automation across both front- and back-office operations, handling large-scale workflows
Approach:
Orchestrator-based architecture, hybrid AI models, integration of multiple LLMs and APIs.
Key strengths:
- High reliability and scalability
- Proven automation rates above 60%
- Multi-million dollar ROI for clients
Use cases:
AI agents for contact centers, fintech, and telecom automation solutions.
9. SoundHound – Voice-First AI Agents
SoundHound specializes in voice-first AI agents built on the Amelia 7.0 platform, with a strong focus on healthcare and patient interaction.
Key focus areas:
Voice-first AI agents, advanced NLP for speech understanding, and conversational voice systems for customer/patient engagement.
Approach:
Speech recognition, voice-centric UX design, and multimodal dialogue capabilities.
Strengths:
- High level of interaction and user engagement
- Widely adopted in healthcare, with ~200 medical institutions using their solutions
Use cases:
Voice assistants are deployed in healthcare facilities for consultations and patient support.
10. Cohere – Enterprise‑Scale Generative & Agentic AI Agents
Cohere offers a powerful LLM-based platform delivering agent solutions tailored for the healthcare and finance sectors, with deep integration into enterprise ecosystems.
Focus areas:
- Generative AI agents, Aya Vision, and other advanced LLM solutions
- Integration with major enterprise systems like Oracle, Salesforce, and Dell
Approach:
LLM fine-tuning, retrieval-augmented generation (RAG) agents, and enterprise-grade deployment.
Key advantages:
- Trusted by large corporate clients
- High scalability and robust multi-agent orchestration
Use cases:
AI agent solutions for the finance and healthcare sectors featuring deep LLM integrations and contextual reasoning.
| Company | Core Focus | Key Strengths | Typical Clients / Industries |
| SCAND | Custom agents, voice and NLP assistants | Flexibility, security, Agile approach | Fintech, Healthcare, Logistics, eCommerce, Retail, Legal, Telecom, Big Tech integrations |
| Deviniti | Secure, self-hosted agents for regulated industries | Full data control, compliance | Finance, Legal, Compliance-heavy sectors |
| Master of Code | Conversational AI, enterprise multi-agent | End-to-end delivery, ISO 27001 certification | Global brands, CRM/ERP integration |
| ManoByte | B2B-oriented agentic solutions | Strong business alignment, process orchestration | Mid-market / Enterprise B2B |
| SoluLab | Multimodal agents for cross-industry use | Flexibility, Fortune 500 clients | eCommerce, Fintech, Healthcare |
| Markovate | Marketing & conversational agents | Conversion marketing, personalization | Retail, eCommerce |
| 10Clouds | Product-led AI agent solutions | UX + ML expertise, fast product launch | Startups, SMEs, product teams |
| NICE | Automating enterprise CS workflows | Orchestration, high automation rates | Telecom, Contact Centers, Finance |
| SoundHound | Voice-first agents, Amelia platform | Voice interfaces, patient engagement | Healthcare, Voice-centric environments |
| Cohere | Enterprise generative + multi-agent systems | LLM fine-tuning, scalability, integrations | Finance, Healthcare, Big Tech integrations |
Top AI Agent Development Companies in 2025: Focus Areas, Strengths, and Industry Fit
Why SCAND Is One of the Best AI Agent Development Companies in 2025
While many companies are just beginning to explore the potential of AI agents, SCAND is already integrating them into real-world business processes. These aren’t experiments or chatbots created just for show — they are well-designed, intelligent systems that truly deliver: engaging with customers, assisting employees, streamlining operations, and generating measurable results.
What makes SCAND stand out? First, experience: with over 25 years in software development and dozens of AI projects, SCAND brings deep technical and domain knowledge.
Second, the approach: every agent is tailored to the client’s specific needs, infrastructure, industry regulations, and business goals.
Third, the technology stack: SCAND leverages top-tier tools — from OpenAI and Rasa to LangChain and TensorFlow — and builds architectures that are scalable, integrable, and secure.
That’s why, when businesses look for the best AI agent development company in 2025, choosing SCAND isn’t about following a trend — it’s about achieving real results.
Conclusion
Companies that adopt AI agents in time gain more than just efficiency — they transform their entire business structure, making processes smarter and freeing people from routine tasks. In a few years, this won’t be a competitive advantage — it will be a requirement for survival.
To build such a system, you need more than a vendor — you need an engineering partner. SCAND doesn’t just develop agents — they turn ideas into functional, secure, and scalable AI software solutions. That’s what it means to take technology seriously.
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