Agentic AI Development Services
Build autonomous AI agents capable of reasoning, decision-making, and task execution.
Custom AI agent development for businesses that want to automate complex, multi-step work — not just chatbots. We build agents that reason through tasks, call tools and APIs, make decisions, and execute real work autonomously, wired into your existing systems.
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AGENTIC AI DEVELOPMENT STACK
Technologies we build with
Agent architecture design
Designing the reasoning loop, tool access, memory, and guardrails your agent needs — scoped to a specific job, not a general-purpose assistant that does everything poorly.
Tool calling & integrations
Connecting agents to your CRM, databases, APIs, and internal tools so they can actually take action — not just generate text about what should happen.
Multi-agent systems
Orchestrating multiple specialized agents that hand off work to each other for complex workflows too large for a single agent to handle reliably.
RAG & knowledge systems
Retrieval-augmented generation pipelines that ground agents in your actual business data and documentation, reducing hallucination and improving accuracy.
Guardrails & evaluation
Testing frameworks, output validation, and human-in-the-loop checkpoints so agents operate reliably and safely within defined boundaries.
Deployment & monitoring
Production deployment with logging, cost monitoring, and performance tracking — so you know exactly what your agents are doing and what they cost to run.
Livrables
Nos outils de prédilection
CAPABILITIES
What we build
Customer support agents
Autonomous resolution of common support tickets.
Research & data agents
Autonomous research and report generation.
Sales & outreach agents
Automated prospecting and qualification.
Internal workflow agents
Automating multi-step operational tasks.
RAG knowledge systems
Agents grounded in your business data.
Multi-agent orchestration
Coordinated systems for complex workflows.
Voice agent integration
Combining agentic logic with voice interfaces.
Agent evaluation frameworks
Testing accuracy and reliability before launch.
Chatbot-to-agent upgrades
Evolving static chatbots into real agents.
Ongoing agent support
Retainer-based monitoring and improvement.
Comment nous travaillons.
Un rythme mesuré — pas de surprises, des démos hebdomadaires, des décisions en quelques heures.
- 01
Scoping
Task definition, tool mapping, and architecture design.
- 02
Build
Agent development and tool integration.
- 03
Testing & Guardrails
Evaluation framework, edge case testing, and safety checks.
- 04
Deploy & Monitor
Production rollout with monitoring and cost tracking.
Ce que vous obtenez réellement.
Équipe interne senior
Pas d'intermédiaires. Ceux qui définissent le projet sont ceux qui le livrent.
Démos hebdomadaires, décisions rapides
Sprints de livraison de deux semaines avec une démo publique chaque vendredi. Finies les devinettes.
Conçu pour durer
Stacks typées, tests, observabilité, design tokens — construit pour que la prochaine équipe vous remercie.
WHERE WE WORK
Serving clients worldwide
We partner with startups and businesses across the globe, with dedicated expertise in these markets:
Working across US, UK, European, Gulf, and Asia-Pacific time zones with weekly demos.
FAQ
Frequently asked questions
Cost & scope
A single-agent system starts around $8k, including architecture design, tool integrations, and production deployment. Multi-agent systems and complex integrations are quoted based on scope.
A chatbot generates text responses. An agent reasons through a task, calls tools and APIs, makes decisions, and takes real action — like updating a CRM, booking a meeting, or completing a multi-step process autonomously.
A single-agent system typically takes 4-5 weeks from scoping to production deployment. Multi-agent systems run longer depending on complexity.
Technical & safety
Guardrails, output validation, and human-in-the-loop checkpoints are built into every agent, along with an evaluation framework tested against real scenarios before going live.
Claude and OpenAI models primarily, chosen based on the task — reasoning quality, cost, and latency requirements determine which model fits best.
Yes — through RAG pipelines for knowledge and direct API/tool integrations for taking action, all scoped to only what the agent needs access to.
Collaboration
Every build includes initial post-launch monitoring, with retainers available for ongoing performance tuning, cost optimization, and expanding agent capabilities.
Yes — agents often work alongside n8n workflows and CRM automation we've already built, or can be layered onto your existing systems.