Intelligence · Service
AI AgentsAI agents that understand requests and act inside your systems.
We build agents that retrieve information from your own knowledge, reason through defined workflows, use tools to read and update business systems, and hand over to people when judgement is required.
AI that understands requests, retrieves information and takes action.
What you get
- Retrieval over your knowledge
- Tool use
- Guardrails
- Human hand-off
01The problem
Chatbots answer questions. Your team still does the work.
Most AI deployments stop at a chat window. The customer gets an answer, but someone still has to look up the order, update the CRM, book the slot and send the confirmation.
- Scripted bots that break on anything slightly unexpected
- Generic AI answers that ignore your policies and data
- No connection between the conversation and your systems
- No clear boundary for what the AI may and may not do
02The solution
Agents with knowledge, tools, rules and oversight.
An agent combines a language model with retrieval over your content, a defined set of tools that call your systems, business rules that constrain its actions, and logging so every decision can be reviewed.
- 01
Retrieval over your knowledge
Answers grounded in your documents, policies and data (RAG), with sources.
- 02
Tool use
Scoped functions to look up records, create tickets, update CRMs, book slots or send messages.
- 03
Guardrails
Permissions, validation and confirmation steps on actions that matter.
- 04
Human hand-off
Escalation to the right person with the full conversation and context.
03How it works
From request to result, step by step.
- 1
Understand the request
The agent interprets intent and extracts details like names, dates, order numbers or amounts.
- 2
Retrieve context
It searches your knowledge base and looks up relevant records before responding.
- 3
Decide within rules
It chooses the next step allowed by the workflow — answer, act, ask a clarifying question or escalate.
- 4
Act and record
Tools execute the action in your systems and the outcome is logged for review.
04Typical use cases
Where it fits.
Customer support agents
Resolve common requests end to end — order status, changes, returns, account questions.
Sales and lead qualification
Ask qualifying questions, score leads and book meetings into the right calendar.
Internal knowledge assistants
Help staff find procedures, policies and answers across internal documents.
Operations agents
Monitor queues, triage requests and prepare work for human approval.
Document agents
Read incoming documents, extract data and route them to the right workflow.
Technology
- LLMs
- Agentic AI
- RAG
- Vector Databases
- Python
- TypeScript
- FastAPI
- PostgreSQL
- APIs
Chosen per project for fit, maintainability and cost. No vendor partnership or certification implied.
05Process
How we deliver ai agents projects.
- 01
Understand
Pick the workflow, define what success looks like and where the agent's authority ends.
- 02
Architect
Knowledge sources, tools, permissions, escalation paths and evaluation criteria.
- 03
Build
Agent logic, tool integrations and a test set of real scenarios.
- 04
Integrate
Connect to channels (web, WhatsApp, voice, email) and systems of record.
- 05
Optimise
Review transcripts, tune prompts and retrieval, and expand scope carefully.
06FAQ
Common questions.
What is the difference between an AI agent and a chatbot?
A chatbot mainly answers. An agent can also take actions through tools — looking up records, updating systems, scheduling, sending messages — within rules you define.
How do you stop an agent from giving wrong answers?
We ground answers in your own content, restrict tools to specific permitted actions, validate outputs, require confirmation for sensitive steps and escalate when confidence is low. We also test against real scenarios before launch and review logs after.
Which AI models do you use?
We choose models per use case based on quality, latency, cost and data-handling requirements, and design the system so the model can be swapped later.
Is our data used to train AI models?
We use provider configurations and APIs that don't use your data for model training where such options are available, and we document where data is processed and stored.
Related services, solutions & reading
- ServiceAI AutomationLanguage models embedded into the workflows you already run.
- ServiceWhatsApp AI AgentsSupport, lead qualification and bookings on the channel customers already use.
- ServiceVoice AI AgentsPhone agents that answer, qualify, schedule and route calls.
- SolutionCreate AI assistantsStaff and customers get reliable answers from your own knowledge, and routine requests are handled end to end.
- SolutionAutomate customer supportCustomers get accurate answers quickly, and your team handles the conversations that need a person.
- IndustryHealthcare
- IndustryE-commerce
- IndustryFinance
- IndustryEnterprise
- InsightWhat an AI agent actually is — and when your business needs one
- InsightWhatsApp AI agents for business: how they work and what to plan for
AI Agents
Have a workflow an agent could take off your team's plate?
Describe the requests you receive most often. We'll show you what an agent could safely handle.