What is
Agentic AI?
Quick Answer
Agentic AI is an AI system that can autonomously pursue goals — breaking complex tasks into steps, using tools (APIs, search, databases), making decisions, and executing actions without needing a human to guide every move. It's AI that doesn't just answer questions. It gets things done.
Three Pillars of Agentic AI
Agentic AI systems are defined by three core capabilities that separate them from traditional AI tools.
Autonomous Reasoning
Agents don't just pattern-match. They reason about what steps are needed to achieve a goal — and adapt when something unexpected happens. They can re-plan mid-task if their first approach fails.
Tool Use & Action
Agents can use external tools: browse the web, call APIs, query databases, send emails, update CRMs, read files. Every tool use is a decision — the agent picks the right tool for the right moment.
Memory & Context
Agents maintain context across long sessions and can be connected to a vector database (RAG) so they always have access to your organisation's knowledge — documents, policies, product info, history.
AI Agents vs Chatbots
This is the most common question we get. The answer matters for how you should approach your AI investment.
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Types of AI Agents We Build
Conversational Agents
Talk. Understand. Act.
AI agents that go beyond answering questions. They understand context, remember your business rules, call APIs, update CRMs, and route issues — autonomously.
Process Automation Agents
Observe. Decide. Execute.
Agents that watch for triggers, make conditional decisions, and execute multi-step workflows — without any human clicking a button.
Multi-Agent Systems
Coordinate. Specialise. Scale.
When one agent isn't enough. We design systems where a Planner agent breaks down a task and delegates to specialist agents — each an expert in its domain.
RAG-Powered Agents
Know your business. Always.
Agents connected to your own knowledge — documents, databases, Notion, Confluence, SharePoint. They answer questions using *your* data, not generic training.
Agentic AI By Industry
Real use cases, real outcomes. Not demos — production systems.
Autonomous returns processing + customer contact agent that resolves 90% of tickets without human touch
Document intelligence agent extracts structured data from 10,000 invoices/day with 99.4% accuracy
Patient intake agent qualifies appointments, verifies insurance, and sends pre-visit instructions
AI agent acts as Tier-1 support — reduces support ticket volume by 70% in week one
Lead qualification agent scores inbound enquiries, answers property FAQs, and books viewings
Autonomous screening agent reviews CVs, ranks candidates, and schedules interviews — end to end
How Krinok Builds Agents
From first conversation to production deployment — a repeatable process refined across dozens of agent builds.
Scope & Define
1–2 daysWe map the workflow you want automated — every decision point, tool, and edge case. Most teams are surprised how much is automatable.
Architecture Design
2–3 daysWe design the agent architecture: single or multi-agent, tools needed, memory approach (RAG, in-context, vector DB), and orchestration model.
Build & Integrate
2–4 weeksWe build the agent using your preferred stack — LangChain, LlamaIndex, CrewAI, or custom. We integrate with your existing APIs, CRMs, and databases.
Test & Harden
3–5 daysWe run adversarial tests, edge cases, and failure scenarios. Guardrails, cost controls, and observability are built in — not bolted on.
Deploy & Monitor
OngoingWe ship to production with monitoring, alerting, and a 30-day hypercare window. You get dashboards showing what the agent is doing, and why.
Go Deeper
Explore the specific AI services and knowledge that powers our work.
Frequently Asked Questions
Every real question we've been asked about agentic AI — answered by the team that builds it every day.
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