Question 1

What's the difference between an AI agent and a chatbot?

Accepted Answer

A chatbot talks. An agent acts. Chatbots answer questions based on a knowledge base - they're glorified search with natural language. AI agents read data from your systems, reason through business logic, and execute transactions in your ERP, CRM, or email. They don't just suggest actions; they perform them. That's the difference between a helpful assistant and a digital employee.

Question 2

How is Laava different from other AI consultancies?

Accepted Answer

Most AI shops are 90% data scientists who build impressive demos that never reach production. We're engineers first: equal parts AI/ML, software engineering, integration, and infrastructure. We don't sell strategy decks or 6-month discovery phases. We deploy working systems in 4 weeks. Our measure of success isn't 'cool tech' - it's transactions processed, hours saved, errors eliminated.

Question 3

What industries do you work with?

Accepted Answer

We focus on enterprises with complex processes trapped in documents, emails, and legacy systems. Logistics and supply chain, retail and e-commerce, financial services, public sector, manufacturing. The common thread: high-volume, rule-based work that humans currently do manually because 'it's too complex to automate.' That's exactly where AI agents shine.

Question 4

How long does it take to deploy an AI agent?

Accepted Answer

Our standard engagement is a 4-week Proof of Pilot. Week 1: architecture and integration mapping. Weeks 2-3: build and test with real data. Week 4: shadow mode deployment where the agent works alongside your team before going fully autonomous. This isn't a demo or a POC that sits on a shelf - it's a working system processing real transactions.

Question 5

What happens after the Proof of Pilot?

Accepted Answer

You have options. The agent is yours - we can hand over the code and documentation for your team to maintain. Or we can run it for you: managed hosting, monitoring, and continuous improvement. Most clients start with managed service while building internal capabilities, then gradually take over. No lock-in, no hostage situations.

Question 6

Can AI agents work with our existing systems (ERP, CRM, legacy)?

Accepted Answer

That's the whole point. We don't ask you to rip and replace. Our 3-layer architecture is designed for integration: the Context layer connects to your data sources, the Reasoning layer processes with any AI model, and the Action layer writes back to your systems of record. SAP, Salesforce, Oracle, custom legacy systems - if it has an API or database, we can integrate. If it doesn't, we build the bridge.

Question 7

What about hallucinations and AI mistakes?

Accepted Answer

Every AI system can make mistakes - the question is how you handle them. We build with guardrails: confidence thresholds that route uncertain decisions to humans, citation enforcement that traces every output to source documents, and shadow mode deployment where agents suggest actions before executing them autonomously. Full audit trails mean you can always see why the agent did what it did.

Question 8

Which AI models do you use?

Accepted Answer

We're model-agnostic. Claude, Llama, Mistral - we use whatever fits the task. Complex reasoning might route to a powerful model; simple classification goes to something fast and cheap. This adaptive routing keeps costs down and performance up. We also support on-premise deployment with open-source models for clients with strict data residency requirements.

Question 9

How do you handle sensitive data and security?

Accepted Answer

Data security is architecture, not an afterthought. We can deploy fully within your environment - your cloud, your network, your rules. The AI doesn't need to 'learn' from your data; it reasons transiently and forgets. All integrations use your existing auth and permissions. We provide full observability: every query, every response, every action logged and auditable. GDPR, SOC2, ISO 27001 - we build for compliance from day one.

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