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