Support Agent. Answers common customer questions, and builds context for your teams if it can't answer.
AI Engineering & Adoption
AI does the work. You keep control.
We design end-to-end AI solutions that connect your data, tools and teams. Each solution can combine specialised agents, integrations and human approvals.
We develop AI solutions that empower you
We build infrastructure and workflows that empower your workforce by (1) providing each of your staf with a personal AI agents and/or; (2) building central agents with clear roles. Together, they can carry a workflow from first input to final hand-off, across the tools your team already uses.
Some of the agents we’ve built:
KPI Agent. Compiles live dashboards for management or individual employees from many sources.
Onboarding Agent. Walks new hires through your tools, answering from your own docs & SOPs.
Expense Agent. Checks every expense against your budgets and readies it for approval. Enjoy your meals!
Research Agent. Researches the prospects you are about to meet, so you can focus on closing your next deal.
Marketing Agent. Turns one update into on-brand posts for every channel, drafted in your voice, ready to review.
Quotation Agent. Turns a site visit into a priced quote from your rates and past jobs, ready for you to send.
Order Agent. Reads incoming orders, however they arrive, and enters them into your ERP.
Proven in the field
Not theory. Work we’ve already shipped for clients, running today.
Orka Solaire, 200+ solar sites. Tens of data sources per site; Derriving advanced insights now takes minutes instead of days.
- We unified ~200 site feeds into one secure Data Lake
- Visualisation & Agentic engine allows data analysis
- Recurring tasks that took days now take minutes via Agentic Skills
A tile distributor, zero physical stock. Buyers had to visit the shop and flip through booklets before ordering.
- An agent reads a 1,300-row supplier sheet and makes sense of it
- It groups the mess into 34 products, each with real variants: height, finish, thickness
- Pushed straight into Odoo through MCP, a simple bridge that lets an agent talk to business software directly
- Buyers now browse and order online, and it flows straight into purchasing for delivery
How?
Three stages, with a clear decision before the solution gets more access.
Step 01 Scope
One business outcome is mapped end to end: every agent, tool, data source, decision and human approval it needs.
You agree the success measures, approval points, risks and fixed scope before we build.
- Process/Workflow and decision mapping
- Tool and data access plan
- Success measures
- Risk and approval controls
Step 02 Pilot & Prove
The first working slice runs on real examples in a sandbox, then beside your team with human approval.
We measure quality, time and cost, tune its instructions and tools, and turn failures into repeatable tests.
- Sandbox agent
- Real-example test set + benchmark
- Team pilot with human approval
- Quality, time and cost results
Step 03 Go Live & Improve
The solution goes live gradually, with access limits, logs, monitoring and a clear route back to a person.
Your team gets the documentation and training to own it. We agree the support and tuning period before launch.
- Phased production rollout
- Monitoring and escalation route
- Team training and documentation
- Handover and support plan
Built to be understood
The workflow, infrastructure and model choices stay visible, so your team knows what runs where, what it costs and when a person takes over.
- Workflows connect your tools, data, approvals and escalation paths
- Hosted, private or self-managed infrastructure is chosen around security, sovereignty and cost
- Models are tested per task and routed by quality and price, so expensive capacity is used only where it earns its place
- As the builders of OpenCrane.ai, we are deeply familiar with the sovereign AI principles behind hosting, access and model choice
Some of our {Customer Success} stories
Quentin Ramon
CEO, Orka Solaire NV
Elewa organised our data across ~200 sites into a single secure Data Lake, then gave us personal AI agents that talk to it, transforming our operations. As a solar asset manager, we’re valued for our insights; Elewa expanded the rails to derive them at scale. We couldn't wish for a better partner on this journey.
Why Elewa?
The same principles behind every agent we build.
Several specialised agents can work together across one end-to-end workflow.
Piloted first. Nothing goes live untested
Every decision stays explainable
Elewa’s own marketing engine runs this way: specialised agents share context, pass work between them and keep a human review step before publication.
See the workflow working before you commit
Bring us the process you want to improve. We’ll map the agents, integrations, data and approvals it needs, then show you the first working slice.