AI Agents & Consultation

What we do?

Codot’s AI Agents & Consultation service empowers businesses to deploy intelligent, autonomous software agents tailored to their workflows and data. We design, build, and integrate agents—powered by LLMs and custom logic—that can perceive inputs (chat, APIs, documents), reason over your data, and act across systems. From virtual support assistants and domain-specific knowledge bots to process automation agents and decision engines, our end-to-end approach covers strategy, prototyping, infrastructure, development, deployment, and ongoing optimisation, ensuring reliable, secure, and scalable AI-driven solutions.

Outcomes You Can Expect

Production-Ready AI Agents: Deployed agents integrated with your systems, capable of reliable, autonomous task execution and support.
Improved Efficiency & Responsiveness: Faster handling of queries and workflows, reducing manual intervention and improving user satisfaction.
Actionable Insights: Monitoring and analytics provide visibility into agent interactions, performance trends, and areas for further enhancement.
Scalable Agent Ecosystem: Foundation to add or extend agents for new domains or functions as business requirements grow.
Secure & Compliant Operations: Data privacy and security controls in place, with audit trails and governance for risk management.
Continuous Improvement Path: Ongoing tuning and feature expansion ensure agents remain effective and aligned with evolving needs.

Why Choose Codot?

AI-First Expertise: Skilled in LLMs, vector databases, prompt engineering, and agent orchestration frameworks for robust solutions.
Custom Integration: We connect agents to your existing systems—CRM, databases, APIs, document stores—for seamless, secure operations.
End-to-End Support: From use-case workshops and feasibility analysis to deployment, monitoring, and iterative improvement, we handle every stage.
Security & Compliance: We implement secure data handling, access controls, and audit logging to protect sensitive information and meet regulatory requirements.
Multi-Agent Architectures: Design and orchestrate multiple agents working together—e.g., support bot, analytics assistant, process automator—for comprehensive automation.
Monitoring & Insights: Dashboards and logs track agent performance, user interactions, and errors, enabling proactive tuning and governance.

Engagement Workflow

Discovery & Use-Case Definition: Workshop to identify high-impact agent scenarios, data sources, and success metrics; assess feasibility and ROI.
Architecture & Prototype: Design agent workflows, select LLMs and tools, set up vector DB or retrieval pipelines, and build proof-of-concept agents for validation.
Development & Integration: Implement agent logic, connect to APIs, databases, and external services; develop interfaces (chat widget, API endpoints, CLI) as needed.
Testing & QA: Conduct functionality, performance, and security testing; validate accuracy, response safety, and failover behaviors under varied scenarios.
Deployment & Monitoring: Deploy agents in production or private cloud environments, set up monitoring dashboards, logging, and alerting for health and usage metrics.
Iteration & Maintenance: Analyze usage data and feedback, refine prompts and logic, retrain or update models, and add new capabilities in an agile cycle.