Home / Agentic AI development
Service — Agentic AI
Autonomous agents that plan, call tools, recover from failure, and complete real work — engineered end to end, not demo-grade wrappers around a prompt.
An agentic AI system doesn't just answer a question — it pursues a goal. It decomposes a task into steps, chooses and calls tools (APIs, databases, browsers, internal systems), evaluates its own output, and retries or escalates when something goes wrong. That last part is where most agent projects die: a demo agent that works 80% of the time is a liability, not a product.
At Aivetech we build agents the way backend engineers build services — with typed tool contracts, bounded loops, structured logging of every decision, timeouts, fallbacks, and human-in-the-loop checkpoints wherever the cost of a wrong action is high. The result is an agent you can put in front of customers or run inside your operations without babysitting it.
Typical agentic systems we ship include customer-operations agents that resolve tickets end to end, research and enrichment agents that gather and structure data from many sources, back-office agents that reconcile records across systems, and orchestrator agents that coordinate multiple specialised sub-agents. Many of these sit on top of a retrieval layer so the agent reasons over your data, not just its training set, and plug into an automation backbone for triggers and side effects.
Every project is principal-led and fixed scope. We start with a scoping call to identify one workflow where an agent carries real load, define success criteria and failure budgets, then ship a first production version in 2–4 weeks. From there we instrument, measure, and expand the agent's authority gradually — the same way you'd promote a new team member.
Agents with typed, validated tool contracts — databases, CRMs, internal APIs, browsers — with permissions scoped per tenant.
Planner/worker architectures where specialised agents hand off tasks, with a supervisor that enforces budgets and stops runaway loops.
Every agent ships with an evaluation harness, failure-mode tests, structured traces, and human-approval gates for high-risk actions.
FAQ
Agentic AI development is the engineering of autonomous AI systems (agents) that can plan multi-step tasks, call external tools and APIs, evaluate results, and recover from errors to complete a goal — as opposed to a chatbot that only generates a single reply.
At Aivetech, a first production version of a scoped agent typically ships in 2–4 weeks. Complex multi-agent systems with deep integrations take longer, but we always ship a working production slice first rather than a long prototype phase.
We use bounded execution loops, typed tool contracts with validation, per-action permission scopes, spend and step budgets, structured logging of every decision, and human-in-the-loop approval gates for any action above a defined risk threshold.
We are model-agnostic and choose per workload — frontier APIs or open-weight models — and we favour thin, auditable orchestration code over heavy frameworks so the system stays debuggable and portable.
Book a scoping call. We'll identify one workflow, define success criteria, and ship a production agent in weeks — fixed scope, principal-led.
Book a call →