We design, build and embed AI agents that actually work in production — not experiments sitting in a lab. AI creates measurable value only when the operating system around it is ready to support it. We diagnose, redesign and deploy — together.
The market is flooded with strategy decks. What's scarce is the ability to take agents from concept to production — and keep them there.
Horizontal copilots and chatbots scale quickly but deliver diffuse, hard-to-measure gains. The value is in vertical agents — purpose-built systems embedded in specific workflows — and those require a different kind of partner.
You need someone who understands both the business context and the technical architecture. Someone who has designed workflows for complex organisations for over two decades — and now applies that same discipline to building AI agent systems.
That's what Mindalizer does.
These aren't hypothetical. They are outcomes documented in published AI deployment case studies and industry research across these sectors. The question is: which of these is your next breakthrough?
Seven specialised AI agents collaborate on a single insurance claim — each handling a distinct task such as document parsing, fraud detection, policy lookup, and approval routing. Claims that took days are now resolved in hours.
AI agents independently handle common requests — accessing account information, resolving issues end-to-end, and escalating only edge cases. Human agents focus on complex interactions that genuinely need them.
Agents qualify inbound leads against ideal customer profiles, enrich data from multiple sources, personalise outreach at scale, and hand off only high-intent prospects to the sales team — with full context loaded.
Agents cross-reference patient history, clinical literature, and imaging metadata to surface relevant signals before a physician review. They don't replace clinical judgement — they make it faster and better-informed.
Agents continuously monitor inventory levels, supplier lead times, and demand signals — automatically triggering reorders, rerouting shipments, and alerting operations teams only when human intervention is genuinely needed.
Multi-agent pipelines that research markets, synthesise competitor intelligence, draft deliverable structures, and run quality checks — compressing weeks of analyst work into hours and letting senior talent focus on insight and client relationships.
Sources: McKinsey Insurance 2030 · McKinsey GenAI Economic Potential, 2023 · Gartner Supply Chain Research · Salesforce State of Sales
A 15-node multi-agent pipeline: three parallel enrichment agents feed an AI orchestrator, which scores each lead and routes it — hot prospects to a personalised outreach agent, cold leads to an automated nurture sequence. Live. In production.
We work as a boutique partner — small team, senior attention, zero subcontracting. Every engagement is built on operational reality, not PowerPoint.
We map your workflows, data flows, and decision points to identify where AI agents create the highest leverage. Output: a prioritised roadmap with business-case estimates — not a generic framework.
We design and deploy purpose-built AI agents — single-task or multi-agent architectures — integrated with your existing systems. We build for reliability, not demos. Agents go live and stay live.
Technology alone doesn't transform organisations — people and processes do. We redesign the surrounding workflows, train teams, and establish governance so AI agents create lasting change, not isolated features.
We implement monitoring frameworks, refine agents based on real-world performance, and identify adjacent use cases. The first agent is the beginning — a well-governed agent programme compounds over time.
Our approach combines 20+ years of organisational consulting methodology with native AI engineering capability. Structure and intelligence — applied together.
We assess your current-state operations, data maturity, and workflow architecture to identify the highest-value agent opportunities.
We architect and build the agent systems using n8n, OpenAI/Claude APIs and your existing tools, then run structured pilots with real users before full rollout.
We establish the operating model — KPIs, monitoring dashboards, escalation protocols — to ensure agents continue to improve and scale confidently.
We're not a staffing firm. We're not a software vendor. We're a boutique consulting firm — and that distinction matters when building systems that touch your operations.
We don't produce strategy decks and leave. We stay through design, build, integration, and go-live — until the agent is operating reliably in production.
Rui Pereira brings 24+ years of experience in financial services, customer experience, and operational transformation — the context that makes agent design genuinely fit for purpose.
Your team understands what's built and why. We design for transferability — you own the system, the data, and the knowledge to evolve it without dependency on us.
No 12-month discovery phases. Our structured method moves from diagnosis to first deployed agent in weeks — with measurable outcomes at each phase gate.
Headquartered in Lisbon, operating across Europe and beyond. We bring the rigour of European consulting tradition with the agility of a focused boutique.
We structure engagements around results — not hours billed. Milestones tied to working deliverables keep both sides focused on what matters: measurable business impact.
Everything you need to know about working with Mindalizer on AI agents.
Written by Rui Pereira, Founder & Principal Consultant · Atlassian & n8n Certified · Updated April 2026
Let's spend 30 minutes mapping where an AI agent — built inside a system designed to support it — could create real, measurable impact in your organisation. No commitment, no pitch deck.
