Support
Recurring customer questions
Classify messages, retrieve order context and prepare draft replies. People stay in control of exceptions, refunds and tone.
AI implementation · custom software
Silvant. Every founder and director knows AI and agents will become part of the company. The question is no longer if, but how.
Silvant turns that pressure into a first working process: which work suits AI, which data is needed, where people stay in control and what should be built first.
For support, operations, finance and reporting. With integrations into CRM, ERP, ticketing, databases and the tools your team already uses.
Process first
We do not choose a model before it is clear which process creates value and who owns it.
Existing systems
Integrations with CRM, ERP, ticketing, databases and the tools your team already uses.
Human control
AI prepares, classifies or flags. Decisions stay with people where needed.
Operation after launch
Monitoring, refinement and further development when processes, data or users change.
When AI adds value
Start with the process.
AI works well only when the process is clear. That is why we look at workflow, data, exceptions, rights and ownership before building anything.
Work pressure
Teams lose hours every week to searching, checking, handovers or preparing the same communication again.
Scattered data
Important information lives across CRM, ERP, ticketing, databases, mail or loose exports.
First step
The Quickscan shows which workflow deserves build time, which data is needed and what should not be built yet.
Where this fits
For teams with enough process pressure.
Silvant fits when AI is no longer a tool question, but a process question. Which work consumes capacity every week, which data is usable, and where should human control deliberately remain in the design?
Operations
Daily exceptions
Orders, tickets or tasks that need attention come together in a morning view with owner, missing data and proposed next step.
Finance
Checks before approval
AI flags deviations, retrieves context and prepares proposals. Finance keeps the decision, with logging and clear escalations.
Good fit
Growing teams with enough volume and a process owner who can define what good enough means.
First proof
We calculate with hours now lost to searching, checking, handovers and reporting.
Control
Decision risk, rights, logging and human approval are designed up front.
What we do
One team, three disciplines.
Stap 01
Analysing
We map your processes, systems and data flows. Where does delay appear, which information is missing, which steps take too much attention and where can AI support reliably?
Stap 02
Building
We develop the solution to fit: an AI feature, internal tool, workflow or integration that matches your existing software and the way your team works.
Stap 03
Operating
After delivery we stay involved. We monitor usage, quality and integrations, adapt when processes change and keep improving when new opportunities appear.
Philosophy
Custom work around the process
Technology should fit.Not the other way around. That is where good custom work starts.
A good AI solution fits the reality of your organisation: the exceptions, systems, responsibilities and people who need to use it. That is why we design around the process, not around the tool.
Anonymous client case
E-commerce as flagship proof.
For an e-commerce company with 20+ employees, we brought dozens of data sources, internal knowledge and recurring workflows together in a custom environment. E-commerce is an important proof area for Silvant because support, operations, stock, reporting and commercial decisions quickly come together there.
Sector
E-commerce
Scale
20+ employees
Data sources
Dozens of sources brought together
Adoption
AI workflows in daily use
What was built
BI and central data layer
A custom BI dashboard and central data layer replaced loose exports and scattered analytics tools.
Company brain
Internal knowledge, context and ways of working became searchable and useful for daily questions and decisions.
Workflow support
Customer service, VA workflows, reporting, analytics and recurring operational tasks were supported with AI workflows and automations.
What it delivered
Direct
Tens of thousands of euros in direct cost savings.
Commercial
New sales channels could be opened faster.
Daily
Less friction through less searching, fewer context switches and faster preparation work.
The client name intentionally remains anonymous. Measurable amounts are used only where they can be tied to direct savings; broader productivity gains are described qualitatively.
View use casesScenarios
Processes with enough repetition.
The practice case shows how Silvant works when data, knowledge and workflow come together. Below are recognizable process patterns where the same approach often creates value.
Support
Responding faster to customer questions
AI classifies messages, retrieves context from systems and suggests a reply or next step. The team stays in control of exceptions and tone.
Less search time across ticketing, CRM and ERP
Logistics
More grip on daily planning
An internal overview shows which orders, tickets or tasks need attention. Teams start the day with priorities instead of scattered exports.
Stand-up starts with choices instead of exports
Retail
Stock, purchasing and reporting
Data from sales, stock and suppliers is brought together in one reliable overview. Decisions are based on current information.
One source for important choices
Who we work with
For organisations that want practical AI.
We work with companies that have enough process volume to implement AI seriously: teams losing time to recurring investigation, checks, handovers and reporting.
What
AI software, internal tools and integrations · from analysis to operation
For whom
Growing organisations with clear process owners and enough volume for custom work
Where
E-commerce, support, operations, finance, planning, reporting and internal workflows
Region
All of Europe
Role
Technical partner for design, build, implementation and operation
When it fits
When custom work makes sense.
Silvant fits when standard software does not quite match, data is scattered or teams have enough manual work for a custom solution to pay back.
QuickscanGood fit
There is a clear process, enough volume or impact and a process owner who can define what good enough means.
Poor fit
There is not yet a process owner, usable data or clear workflow to design around.
First step
A Quickscan turns process, data, value, risk and the first build step into a concrete decision.
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