Read
Context from systems
The agent uses customer data, order status, tickets, documents, rules or exports to place a task in context.
AI agent development
Build an AI agent that fits the process.
Silvant builds AI agents that prepare work, retrieve context, propose next steps and queue actions within clear limits. Not a standalone chatbot next to operations, but software around the systems your team already uses.
Fit
When an AI agent makes sense.
An agent deserves build time when the task recurs, needs context and has risks that can be made visible or bounded.
Strong candidate
The process happens daily or weekly and uses context from multiple sources.
Custom needed
A standard tool lacks system access, rights, workflow logic or operation after launch.
Too early
The task is unclear, data is unreachable or no one owns exceptions and feedback.
Agent stack
What we build.
Propose
Prepare work
Summaries, priorities, draft replies, exceptions or next steps are prepared for review.
Bound
Control by design
Write access, customer impact, money, privacy and exceptions get approval, logging and escalation points.
Approach
From candidate process to first agent.
Stap 01
Select process
We choose a recurring workflow with enough volume, clear output and an owner who can provide feedback.
Stap 02
Map context and systems
We identify the minimum sources: CRM, ERP, ticketing, documents, databases, exports or internal tools.
Stap 03
Design control
We define what the agent may read, propose, queue or execute, and where human approval remains required.
Stap 04
Launch first build
The first version is deliberately narrow: real enough to touch work, small enough to test, correct and operate.
Scope
What defines scope.
Systems
Number of integrations, APIs, exports, data sources and the quality of those sources.
Autonomy
Reading and proposing is smaller than executing actions or writing data back.
Governance
Rights, logging, audit trail, approval flow, evaluation and operation after launch.
FAQ
Frequently asked questions
Is an AI agent the same as a chatbot?
No. A chatbot mostly handles conversations. An AI agent works inside a process, uses system context and can prepare work or queue actions within agreed limits.
When is an AI agent too early?
When the process is unclear, data is unreachable, risk cannot be bounded or no one owns feedback and exceptions.
Should an agent act autonomously from day one?
No. The first version often starts better by reading, summarising, flagging and proposing. Autonomy comes after context, logging and control work.
What is the first step?
The Quickscan turns process, data, systems, risk and the smallest useful first build into a concrete decision.
Further reading
Do not read this alone.
Contact
Process, data, build
Start with the Quickscan.
In a short analysis we look at your processes, systems and data. Afterwards you know where AI can add value and which solution is logical to build first.
Coverage
Working across Europe
Hours
Mon-Fri · 09-18 CET
E-mail
hallo@silvant.ai
First step
Quickscan