AI that works
with your business.
Agents, chatbots and automation connected to your customers, knowledge and business systems. Built around a real workflow, not another isolated tool.
Founder-led. From the first workflow to the integrations that make it useful.
Where should AI
get to work?
Choose a starting point. These are example project scopes, shaped around your data, tools and approval rules.
A helpful answer.
A useful next action.
Connect a customer request to the right order, product or policy. Draft a grounded response, route exceptions and keep the next person’s context intact.
- Incoming request
- Order + policy context
- Draft or route
- Approved action
- A first release
- One channel, one request category, verified sources and a clear handover to your team.
- What we check
- Answer accuracy, unresolved cases, review time and appropriate escalation.
Your knowledge.
Ready when it’s needed.
A company knowledge assistant that searches approved documents, explains what it finds and links back to the source. With access boundaries and a way to say “I don’t know.”
- Team question
- Permitted sources
- Answer + citations
- Verify or escalate
- A first release
- One audience, an owned document collection, source refresh and a realistic question set.
- What we check
- Source relevance, grounded answers, permission boundaries and missing knowledge.
From incoming files
to checked records.
Turn recurring invoices, purchase orders or delivery notes into structured information. Validate the fields, review exceptions and connect approved records to your ERP.
- Receive a document
- Extract + validate
- Review exceptions
- Verified ERP draft
- A first release
- One document family, a defined record schema, an exception queue and a verified destination write.
- What we check
- Field accuracy, duplicate prevention, review effort and cost per accepted document.
Less chasing.
More work moving.
Connect requests, CRM tasks and internal systems into a controlled workflow. Use AI for interpretation, rules for predictable steps and people for consequential decisions.
- Business request
- Interpret + match
- Validate + approve
- Update + reconcile
- A first release
- One recurring job, a bounded set of tools, an approval step and a usable failure queue.
- What we check
- Completed tasks, correction effort, integration failures and operating cost.
Useful first.
Then scale.
We scope the AI and the systems around it together. The first phase should answer whether the workflow is worth expanding.
Find the right first job.
Map the current process, establish a baseline and agree the outcome. If a simpler integration is enough, that’s what we scope.
Workflow brief · Data readiness · Success criteriaBuild a controlled pilot.
Connect the permitted sources and tools. Test real cases, exceptions and approvals with the people who will use it.
Working pilot · Evaluation · Review pathPut it into practice.
Launch with monitoring, documentation and a manual fallback. Agree ownership, running costs and the next improvements.
Handover · Operating costs · Support plan
Measure completed work, quality and remaining human effort. Not just how convincing the demo looks. Explore the ROI framework
Connected systems
are what we build.
Founder-led experience across commerce, growth and operations, backed by Waslio products you can explore. The same delivery discipline matters when AI becomes part of a business workflow.
What should AI
take off your plate?
You don’t need a technical brief. Tell us what repeats, where the information lives and what you want to happen instead.
- We review your workflow and reply within one business day.
- We agree a useful next step, usually a short discovery call.
- You receive an agreed scope and price before any build starts.
Prefer email? founder@waslioconnect.com
Before we start.
Can you work with our existing tools?
That’s the starting point. We assess your CRM, ERP, ecommerce platform, documents and available APIs before proposing a solution. Access, licenses and integration limits are checked during scoping.
Do we need to know which AI model to use?
No. Start with the job and the quality you need. Model choice, retrieval and integration architecture follow from your workflow, data requirements and operating budget.
How much does an AI project cost?
Cost depends on the workflow, source quality, integrations and review requirements. We scope the first phase before quoting and distinguish implementation from ongoing model, infrastructure and support costs.
What about sensitive data and approvals?
We define permitted data, access controls, retention and human review before connecting production systems. Consequential actions need explicit controls. Please use sanitized examples in your initial enquiry.

