One platform for AI agents that
work.
Laava connects business context, systems, and secure actions in one operational AI platform. Our Forward Deployed Engineers bring the first workflow live and build from there.
Start with one workflow. Keep the context, tools, governance, and operational learning for every agent that follows.
Positioning
More bots do not make an intelligent company.
The first demo is rarely the hard part.
Production agents need current context, controlled access to systems, explicit approval rules, evaluation, monitoring, and an owner when something changes.
Laava turns those requirements into one reusable platform instead of rebuilding them for every workflow.
Platform architecture
One operating system behind every agent
The first workflow establishes the shared context, tools, and controls. The next workflow reuses that foundation instead of starting as another isolated build.
Reuse loop
Existing operation
Context and data
01Approved sources, ownership, provenance, permissions, and current operational state.
Safe tools and actions
02Scoped reads, proposals, approvals, and writes into the systems the business already runs.
Agents and workflows
03Specialised agents across chat, voice, email, tickets, web, and APIs within the agreed Launch scope.
Control and operations
Identity, human review, evaluations, logging, incidents, changes, releases, rollback, ownership, and cost are handled as part of the production system.
Deployment follows the workload
Laava Managed
Standard scoped route
Customer Cloud / VPC
After architecture and responsibility review
Laava Box
Paid design-partner route
Four specialised roles
One foundation underneath them all
Lighthouse implementation
One AI operation. From customer call to back-office follow-up.
OpenSource Energie runs voice, chat, service-ticket, and collections workflows on one shared foundation, connecting context, tools, controls, and human handovers.
Less routine work for the team. Recurring steps in customer contact and follow-up shift from people to agent workflows. People keep the exceptions and the judgment calls.
Available 24/7. Digital workflows keep customer work moving, with human handoff where judgment is needed.
Approach
From one workflow to operational AI capacity
A commercial path that keeps delivery and product adoption connected.
Step 01
Prove one workflow
Define the bottleneck, business owner, systems, source of truth, actions, risks, and a measurable success gate.
Step 02
Launch on the platform
Set up the workspace, identity, context sources, tools, agent, evaluations, monitoring, and operational runbook.
Step 03
Operate and improve
Track quality, usage, cost, incidents, model changes, and human corrections. Every change stays reviewable and reversible.
Step 04
Expand with an FDE
Reuse the existing context, tools, and controls to bring the next workflow live faster.
Choose the deployment that matches the work
Private and secure are architecture outcomes, not marketing adjectives. We choose the profile after mapping data, availability, access, and operations.
01
Managed EU environment
An environment managed by Laava within an explicitly agreed European hosting, access, and service scope. This is the standard scoped route.
02
Your cloud or VPC
The platform may run in the customer cloud boundary after architecture, security, operating responsibility, and economics have been reviewed.
Laava Box on premises
A paid design-partner route for hard physical-location, offline, local-network, or operational-control requirements. Delivery follows a separate readiness assessment.
Forward Deployed Engineers make the platform useful.
An FDE works with a domain owner inside the operation, owns the path to production, and turns each implementation into reusable context, tools, evaluations, and runbooks.
You get somebody close to the work, backed by Laava's platform and specialists.
Questions
What companies ask before adopting the platform
Discuss your first workflow
Bring one recurring process, the systems involved, and the outcome you want. We will assess the first agent, platform fit, and the most sensible deployment profile.
Response time
We typically respond within 24 hours