Gradient Logic Let's talk

Gradient Logic

We design and build AI systems that actually ship.

From enterprise AI strategy to production-ready products. Idea to deployed AI in weeks, not quarters.

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Based in Athens · Leading AI transformation for a global engineering enterprise

What we bring

  • AI strategy & architecture for organizations scaling beyond pilots
  • Agents, RAG and copilots to production with evals and monitoring
  • Hardware and infra specs for hosting local LLMs on-prem
  • Security-first: GDPR, guardrails, governance and access control
  • StoreMate AI: a turnkey assistant for physical stores

What we do

Two modes: hands-on consulting for enterprises and a turnkey product for brick-and-mortar stores.

AI Strategy & Architecture

Use-case discovery, ROI modeling, technology selection and roadmap design. Includes specs for on-prem hosting of local LLMs. For organizations starting or scaling their AI journey.

  • Use-case prioritization
  • Enterprise architecture
  • Hardware specs for local LLMs
  • Vendor & model evaluation
  • Team enablement

Implementation & Integration

Building agents, RAG systems, MCP tooling and copilots. From prototype to production with evaluations, security and monitoring.

  • Agentic workflows & MCP servers
  • RAG & knowledge platforms
  • On-prem / local inference where it is required
  • Evals, guardrails & governance
  • CI/CD & observability

StoreMate AI

Turnkey AI assistant for physical stores. Crawl any website, build a knowledge base, deploy a customer-facing chatbot.

  • Automated web crawling
  • Menu & price extraction
  • Multilingual chat
  • Self-service setup

Current work

Enterprise Engagement

Leading AI transformation for a global engineering enterprise

Designing and leading the corporate AI approach for a multinational engineering company with operations across 50+ countries: from strategy and reference architecture through agent platforms, MCP, RAG and governance.

In progress

On-prem hosting for local LLMs

Hardware and infrastructure specs so a large organization can run local LLMs on-prem: GPU sizing, inference stack, capacity planning and privacy requirements.

StoreMate AI

Our product: AI assistant for restaurants, cafes and retail. Automated crawling, knowledge base and multilingual customer chat.

Details

Selected work

  • Wholesale operations intelligence: Sales & inventory dashboards on ERP data: CSV/API sync to actionable KPIs for leadership.
  • Industrial technical knowledge assistant: RAG over a private technical library (PDFs, diagrams) with RBAC, citations and an audit trail.
  • B2B commerce sales assistant: Wholesale sales assistant: SKU understanding, availability, product recommendations (GR + EN).
  • Transfer Service Copilot: Lead triage & itinerary builder. 60% faster response, 18% conversion lift.
  • B2B SaaS Knowledge RAG: Unified product docs + support tickets. Search time: minutes to seconds.

StoreMate AI

An AI customer assistant for restaurants, cafes and retail. Paste a URL, get a trained chatbot in minutes.

Automated Crawling

Scans the store's website, finds PDF menus, extracts every item with prices.

Knowledge Base Generation

Structures everything into a clean KB: menu, hours, location, reviews, FAQs.

Multilingual Chat

Customers chat in any language. Answers from the KB only, with no hallucinations.

How it works

  1. Paste URL: Enter any store website. Add extra PDF links if needed.
  2. Crawl & Extract: AI discovers pages, PDFs, menus. Extracts every item, price and detail.
  3. Review KB: See the structured knowledge base. Edit, add missing info, re-index.
  4. Chat: Customers ask questions. The AI answers from the KB in any language.

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How we work

  1. Discovery: Map your pains, data landscape and quick wins. Define measurable outcomes. We leave with a ranked backlog and success metrics, not a workshop deck.

    Output: Ranked backlog + success metrics per business unit

    • Use-case prioritization inside a global engineering enterprise (50+ countries)
    • Data landscape: ERP feeds (CSV/API), private technical libraries, product docs + support tickets
    • Quick-win signals from wholesale ops, B2B sales assist and transfer-service triage
    • Outcomes set early: response time, conversion, search latency
  2. Design: Architecture, guardrails, evaluation plan. Security and compliance from day one. Interfaces and failure modes are explicit before production code.

    Output: Reference architecture + guardrails + evaluation plan

    • Enterprise AI architecture: agent platforms, MCP tooling, knowledge systems
    • Hardware and infra specs for on-prem hosting of local LLMs
    • Security model: RBAC, citations, audit trail (industrial technical RAG)
    • Privacy-first / GDPR patterns for customer and internal assistants
    • Eval plan and failure modes before the first production deploy
  3. Build: Prototype in days, iterate to production with evals and monitoring. Each loop tightens quality gates until the system is safe to ship.

    Output: Production system with evals, monitoring and quality gates

    • Pilots to production: technical knowledge RAG, B2B sales assistant, SaaS knowledge platforms
    • Product loop as in StoreMate: crawl → KB → multilingual chat grounded on the KB
    • Observed lifts: ~60% faster response, +18% conversion, search from minutes to seconds
    • CI-friendly evals and observability instead of one-off demos
  4. Scale: Handover, team enablement and roadmap to expand ROI across the organization. Playbooks and ownership so the next use cases do not restart from zero.

    Output: Enablement program + ownership model + expansion roadmap

    • Corporate AI strategy and reference architecture across multiple business units
    • Team enablement so internal teams can run the next use case without a reboot
    • Reusable playbooks for agents, RAG and governance across geographies
    • Handover with a measurable ROI path, not a closing slide deck

About

Gradient Logic is a boutique AI consultancy led by Pavlos Polydoras, based in Athens. We combine hands-on engineering with strategic advisory to ship AI systems that create real business value, not just impressive demos.

Currently serving as AI Strategy Lead for a global engineering enterprise, designing and implementing their corporate-wide AI approach across multiple business units and geographies, including agent platforms, MCP servers, knowledge systems and governance. In parallel, we are shaping hardware and infra specs for on-prem local LLM hosting at a large organization.

  • Deep experience with RAG, agentic workflows, MCP and LLM evaluations
  • Production systems with Claude, GPT-5.6, Gemini and open-source models
  • Hardware specs and on-prem hosting for local LLMs
  • Privacy-first architectures aligned with GDPR best practices
  • Full-stack: Next.js, Python, TypeScript, Postgres, vector databases

Tech we work with

  • LLMs: Claude, GPT-5.6, Gemini · open-source: GLM-5.2, Mistral, Llama, Phi
  • Frameworks: LangChain, LlamaIndex, MCP, custom agents
  • Infra: Next.js, Python, Postgres, ChromaDB, Pinecone, Qdrant
  • Platforms: Vercel, Cloudflare, AWS, GCP, on-prem GPU / local inference

Let's talk

Tell us about your goals and we'll suggest a focused starting point.

Get in touch

Good fit if you need

  • AI strategy for your organization: where to start, what to build
  • Agents, RAG, MCP, or copilots built and deployed to production
  • Hardware specs and on-prem hosting for local LLMs
  • An AI customer assistant for your store, restaurant, or cafe
  • A technical advisor who has shipped real AI systems at enterprise scale

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