Senior Product Manager | AI, SaaS, and Data Platforms

Matt Ghoreishi

I build products where AI, data, and business outcomes meet.

Senior Product Manager based in Hamburg, working across AI-enabled workflows, SaaS and data platforms, monetization, dashboards, and evaluation systems, with a focus on turning product bets into shipped outcomes.

Product leadership profile

Strategy that survives the handoff to execution.

I work where product bets need to become usable systems: scoped workflows, clear metrics, quality bars, stakeholder alignment, and the operating details that make a launch hold up after the demo.

AI product strategy
SaaS and data platforms
Monetization and growth
Evaluation and quality systems
Dashboards and operational visibility
Product execution across teams

Featured writing

The Agentic AI Product Gap

Why the hard part starts after an agent gets the first task right

13 min read

A practical argument that agentic AI becomes product work when systems move from answering to acting. The article introduces the Agentic Product Stack as a way to reason about workflow fit, risk, autonomy, evals, monitoring, governance, and value.

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Featured tool

Agentic Product Stack Mapper

Turn an AI agent idea into a structured Agent Product Brief across workflow fit, risk, autonomy boundaries, evaluation, governance, and business value.

Live

A lightweight workspace for turning an AI agent idea into a structured Agent Product Brief with workflow fit, risk shape, autonomy boundaries, evaluation gates, human control, monitoring, governance, and value.

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Where I create value

Product leadership built through execution.

My work sits between business goals, platform constraints, user workflows, and the evidence needed to ship. I focus on products that can be adopted, measured, operated, and improved after launch.

AI product strategy

Turning ambiguous AI opportunities into scoped product bets, evaluation plans, and launch paths.

SaaS and data platforms

Designing durable product systems with clear workflows, roles, metrics, and operating models.

Dashboards and visibility

Building dashboards, decision layers, and operating views that make product and business health legible.

Monetization and growth

Connecting product strategy to pricing, packaging, adoption, retention, and commercial outcomes.

AI-enabled workflows

Applying AI where workflows, users, risk, quality, and operational value have to work together.

AI evaluation

Treating quality, safety, edge cases, human review, and runtime signals as product requirements.

Enterprise AI delivery

Bringing strategy, stakeholders, quality, governance, and rollout planning into production delivery.

Execution

Moving from strategy to shipped product through prioritization, alignment, and measurable delivery.

Experience across AI, SaaS, and data platforms

A concise product leadership story.

AI and workflow products

  • AI product strategy, roadmap shaping, and MVP planning for workflow-heavy products.
  • Contact Center AI delivery as one example of applying AI inside real operational processes.
  • Evaluation, quality, human review, and runtime monitoring treated as product requirements.

SaaS and data platforms

  • Gas monitoring SaaS and dashboard work focused on operational visibility and decision support.
  • Data-heavy product experiences where adoption depends on clarity, trust, and repeatable workflows.
  • Platform thinking across users, permissions, metrics, and long-term maintainability.

Monetization and marketplace growth

  • Direct Carrier Billing product work with revenue impact and cross-functional execution.
  • VOD, platform, and product growth work across customer experience, distribution, and commercial goals.
  • Ads monetization growth with attention to product mechanics, measurement, and business outcomes.

Product execution and alignment

  • Turning ambiguous business problems into shipped product increments and measurable outcomes.
  • Working across engineering, design, commercial, operations, and leadership stakeholders.
  • Balancing strategy, delivery, quality, and adoption instead of optimizing only for demos.

About

Practical product leadership for AI-shaped work.

I care about the space where strategy becomes shipped product: the workflow, the operating model, the quality bar, the business case, and the details that make a product credible after the demo.

My current focus is AI, SaaS, and data platforms, especially where teams need to connect new technical capability with measurable outcomes, human control, and clear product judgment.

More about how I work

Contact

Contact

Based in Hamburg. LinkedIn is the best place to reach me for product conversations and collaboration.