agent ia

Develop an AI Agent Tailored to Your Workflows

Integrating artificial intelligence is no longer limited to simply automating repetitive tasks. Today, choosing to develop an AI agent allows you to embed a true virtual team member into your information system. Capable of reasoning, analyzing your internal data in real time, and making autonomous decisions based on your business rules, AI agents redefine operational efficiency for enterprises.

At Esokia, an international digital agency with over 15 years of software engineering expertise, we design custom, secure artificial intelligence agents perfectly aligned with your strategic goals.

Why Develop an AI Agent for Your Enterprise?

Unlike traditional chatbots based on rigid rules, an autonomous AI agent uses advanced large language models (LLMs), natural language processing (NLP), and machine learning to complete complex missions without constant human intervention.

Increased Productivity and Cost Reduction

By delegating the execution of repetitive or complex workflows to an AI agent, you free up strategic time for your teams while drastically reducing the risk of human error.

Accelerated and Smarter Decision-Making

Connected to your databases (CRM, ERP, Big Data), the AI agent synthesizes large volumes of information and delivers actionable insights or executes actions directly within your business applications.

24/7 Availability and Seamless Scaling

Whether handling complex customer inquiries or supervising logistics processes, your virtual agents operate continuously with instant response times.

Our AI Agent Solutions Tailored to Your Business Needs

  • Multi-Agent Systems & Orchestration: Coordination of multiple specialized agents working in sync to automate end-to-end complex, cross-departmental workflows.
  • Customer Support & Service AI Agent: Autonomous resolution of complex tickets, multi-channel support, and personalized interactions.
  • HR & Onboarding Copilot AI Agent: Automated CV screening, generation of onboarding journeys, and instant responses to internal queries.
  • Sales & Prospecting AI Agent: Lead qualification, personalized offer recommendations, and automated follow-ups.
  • Data Analysis & Reporting AI Agent: Extraction, consolidation, and generation of financial or operational reports from heterogeneous data sources.

Our Methodology to Develop Your Custom AI Agent

To guarantee the success, security, and profitability of your project, Esokia applies a proven agile methodology:

  1. Audit & Scoping: Analysis of your processes, identification of high-ROI use cases, and definition of key performance indicators (KPIs).

  2. Architecture & Model Selection: Selection of top technologies (OpenAI, Anthropic, open-source LLMs) and industry-leading enterprise cloud AI platforms (Vertex AI, AWS, Azure/Microsoft). We integrate Retrieval-Augmented Generation (RAG) architecture and the Model Context Protocol (MCP) to securely and standardly connect your models to your organization's context and tools.

  3. Development & API Integration: Seamless integration of the AI agent into your existing software ecosystem (Salesforce, SAP, Zendesk, proprietary systems).

  4. Training & Testing Phase: Optimization of prompt engineering, fine-tuning of decision rules, and rigorous security testing.

  5. Deployment & Continuous Improvement: Production rollout, team training, and ongoing performance monitoring.

Why Choose Esokia to Develop Your AI Agents?

  • Technical Expertise & Agility: Our teams of developers and Data Scientists master advanced AI frameworks (LangChain, LlamaIndex, AutoGen).
  • Data Security & Compliance: We strictly apply top security standards (GDPR, encryption) to ensure your strategic data is never used to train public models.
  • Proximity & Flexibility: Our flexible Nearshore/Offshore model ensures an optimal price-quality ratio and responsive project management.

FAQ

Developing an AI Agent with Esokia

What is an AI agent and how does it differ from a standard chatbot?

A standard chatbot answers predefined questions following a fixed script. An AI agent is autonomous: it understands context, sets sub-goals, uses external tools (e.g., executing a search or submitting a form), and carries out complex tasks to achieve the requested outcome.

Is it possible to develop an AI agent without coding skills?

Yes, there are no-code tools available today to assemble simple AI building blocks. However, for complex enterprise needs—requiring deep integrations with your information system, complete confidentiality for your sensitive data, custom multi-agent workflows, or the implementation of the Model Context Protocol (MCP)—custom development by an engineering team remains essential to guarantee security, reliability, and scalability.

How much does it cost to develop a custom AI agent?

The cost varies based on the complexity of the tasks to be performed, the number of required API integrations, and the choice of language models used. Following an initial audit, Esokia provides a clear estimate tailored to your budget and constraints.

How long does it take to design and deploy an AI agent?

A functional Proof of Concept (PoC) can be deployed in 2 to 4 weeks. Full development and end-to-end integration of a custom AI agent generally take between 6 and 12 weeks, depending on the project scope.

Will my company data remain confidential and secure?

Yes, absolutely. We deploy secure architectures featuring strict data isolation. Your internal information is accessed via secure channels (RAG) and is never reused by LLM providers to retrain public models.

Can the AI agent integrate with my current tools (ERP, CRM, databases)?

Completely. Our developers connect your AI agents to your existing software ecosystem (Salesforce, HubSpot, SAP, SQL databases, proprietary APIs) for seamless, real-time synchronization.

What technologies do you use to develop an AI agent?

We rely on recognized frameworks such as LangChain, LlamaIndex, or AutoGen, combined with cutting-edge language models (GPT-4, Claude 3, Llama 3) and vector databases (Pinecone, ChromaDB, Qdrant).

How do you measure the return on investment (ROI) of an AI agent?

ROI is primarily measured by time saved by your teams, increased volume of processed requests, shorter customer response times, and a reduction in operational processing errors.

Can the AI agent be trained on our internal documentation?

Yes, this is one of our primary use cases. Thanks to RAG architecture, the agent delivers precise and contextualized answers relying exclusively on your business guides, PDFs, knowledge bases, and internal procedures.

What support does Esokia provide after deployment?

Esokia provides application maintenance, model performance monitoring, prompt engineering adjustments based on user feedback, and ongoing agent enhancements as your needs evolve.

Take Your Productivity to the Next Level

Don't let your competitors get ahead. Contact Esokia’s experts today to define your use case and design your first custom AI agent.