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- Edit this `README.md` markdown file to author your organization card.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # Martin Technologies LTD Sovereign Large Language Models
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+
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+ **Website:** [martintech.co.uk](https://martintech.co.uk)
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+ **Regions:** UK & EU
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+ **Focus:** Training, deploying, and operating **sovereign** Large Language Models (LLMs) with full data control, real-time performance, and cost efficiency.
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+
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+ ---
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+
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+ ## Mission
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+
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+ We build and operate **sovereign LLMs** for organisations that require **full ownership, auditability, and control** over their AI stack—without compromising on **state-of-the-art capability** or **real-time latency**. Our systems are optimised for **dedicated hardware** to reduce unit economics while delivering predictable performance and strict data boundaries.
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+
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+ ---
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+
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+ ## What “Sovereign” Means Here
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+
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+ - **You own the runtime:** Dedicated single-tenant deployments (cloud, edge, or on-prem) with **no shared inference plane**.
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+ - **You govern the data:** Hard data boundaries, private networking, and explicit opt-in for any data retention. **No training on your prompts** by default.
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+ - **You decide the geography:** Compute and storage pinned to the **UK or EU** with optional **air-gapped** configurations.
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+ - **You can inspect & reproduce:** Open model families, transparent configuration, deterministic builds, and reproducible evaluation pipelines.
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+
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+ ---
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+
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+ ## Models & Training
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+
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+ We specialise in **state-of-the-art open-source** model families and customise them to your domain and latency/throughput constraints:
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+
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+ - **Base & Instruct Models:** General chat, RAG-optimised instruction models, coding, and tool-use variants.
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+ - **Fine-Tuning & Adaptation:** Lightweight LoRA/QLoRA, adapters, and full-stack fine-tuning for domain language, terminology, and stylistic constraints.
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+ - **Alignment & Safety:** Multi-objective RLHF/DPO where required; policy gradients for content filters; evaluation suites aligned with your risk profile.
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+ - **Evaluation:** Task-specific evals (exact-match, BLEU/ROUGE, factuality, hallucination risk, tool-use success), latency SLOs, and cost/quality Pareto frontiers.
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+
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+ > We prioritise openly auditable model families to preserve portability and long-term independence.
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+
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+ ---
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+
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+ ## Real-Time Optimisation on Dedicated Hardware
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+
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+ Our inference stacks are engineered for **low-latency, cost-efficient** operation:
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+
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+ - **Kernel-level acceleration:** FlashAttention-class attention kernels, fused ops, paged KV cache, and continuous batching.
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+ - **Quantisation:** INT8/INT4 & mixed-precision pipelines tuned per layer to balance perplexity vs. latency.
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+ - **Parallelism strategies:** Tensor, pipeline, and context parallelism with NUMA-aware placement.
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+ - **Speculative & constrained decoding:** Speculative decoding, prefix caches, grammar-constrained decoding for structured outputs (JSON/SQL).
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+ - **Memory topology:** KV cache pinning, CPU-GPU offload, NVLink/PCIe bandwidth planning, and pinned host memory for surge loads.
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+
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+ **Outcome:** predictable p50/p95 latency under load, reduced cost per million tokens, and stable throughput on **dedicated single-tenant** hardware.
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+
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+ ---
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+
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+ ## Deployment Options
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+
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+ ### 1) Managed Cloud (UK/EU)
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+ - **Single-tenant** VPC deployments in the UK or EU, private subnets, customer-managed keys (CMK) optional.
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+ - Hard residency guarantees and private endpoint exposure (PrivateLink/private service connect).
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+
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+ ### 2) Physical Edge Compute
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+ - Ruggedised nodes for **branch, factory, vessel, or field** environments.
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+ - **Store-and-forward** telemetry, offline-first inference, and sync when connectivity returns.
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+
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+ ### 3) On-Premises (Air-Gap Optional)
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+ - Delivered as **appliance** or **reference build** (rack spec + BOM).
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+ - Offline provisioning, **no outbound network** requirement, and fully local observability.
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+
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+ ---
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+
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+ ## Access Patterns
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+
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+ - **API Access:** OpenAI-compatible endpoints for chat/completions, embeddings, tool calls, and JSON-mode.
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+ - **gRPC & SSE:** Streaming tokens for real-time UX; back-pressure aware.
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+ - **RAG Tooling:** Connectors for document stores, vector DBs, and safety classifiers.
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+ - **Multi-Tenant at Your Edge:** You define tenants; we enforce strict isolation per tenant within your sovereign boundary.
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+
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+ **cURL**
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+ ```bash
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+ curl -X POST "$BASE_URL/v1/chat/completions" -H "Authorization: Bearer $MARTINTECH_API_KEY" -H "Content-Type: application/json" -d '{
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+ "model": "martintech/sovereign-llm",
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+ "messages": [{"role": "user", "content": "Summarise our latest policy in 5 bullets."}],
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+ "temperature": 0.2,
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+ "stream": true
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+ }'
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+ ```
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+
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+ **Python**
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+ ```python
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+ import os, requests, sseclient
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+
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+ BASE_URL = os.getenv("BASE_URL", "https://api.your_instance_url.co.uk")
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+ API_KEY = os.getenv("MARTINTECH_API_KEY")
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+
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+ payload = {
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+ "model": "martintech/sovereign-llm",
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+ "messages": [{"role": "user", "content": "Draft a GDPR-compliant notice."}],
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+ "temperature": 0.0,
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+ "stream": True
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+ }
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+ headers = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}
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+
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+ with requests.post(f"{BASE_URL}/v1/chat/completions", json=payload, headers=headers, stream=True) as r:
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+ client = sseclient.SSEClient(r)
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+ for event in client.events():
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+ print(event.data)
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+ ```
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+
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+ **JavaScript (Fetch)**
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+ ```js
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+ const res = await fetch(`${BASE_URL}/v1/chat/completions`, {
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+ method: "POST",
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+ headers: {
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+ "Authorization": `Bearer ${API_KEY}`,
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+ "Content-Type": "application/json"
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+ },
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+ body: JSON.stringify({
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+ model: "martintech/sovereign-llm",
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+ messages: [{ role: "user", content: "Generate a JSON receipt." }],
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+ response_format: { type: "json_object" }
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+ })
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+ });
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+ const data = await res.json();
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+ console.log(data.choices[0].message.content);
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+ ```
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+
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+ > The API is **OpenAI-compatible**, so most existing SDKs and clients work with only a **base URL and key** change.
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+
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+ ---
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+
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+ ## Security & Compliance
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+
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+ - **Data Handling:** No prompt or completion retention unless explicitly enabled. Configurable TTLs and redaction.
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+ - **Encryption:** TLS in transit; at-rest encryption with customer-managed keys optional.
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+ - **Network:** Private networking, IP allow-lists, and optional mTLS between services.
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+ - **Isolation:** Per-tenant logical isolation; dedicated hardware optional for physical isolation.
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+ - **Observability:** Privacy-preserving logs and metrics; structured audit events with redaction.
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+ - **Governance:** DPA addendum, data residency controls (UK/EU), and support for customer risk assessments.
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+
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+ ---
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+
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+ ## Cost Optimisation
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+
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+ - Right-sized model families per use case (tiny → large) with **policy-based model routing**.
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+ - Quantisation and continuous batching to reduce **cost per million tokens**.
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+ - **Cache-aware RAG** to minimise context length and I/O.
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+ - Performance budgets and autoscaling tied to your **SLOs** rather than best-effort throughput.
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+
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+ ---
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+
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+ ## Typical Use Cases
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+
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+ - **Private Assistants** for regulated teams (legal, finance, public sector).
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+ - **RAG over Sensitive Corpora** with strict data residency.
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+ - **Structured Generation** (JSON/SQL) into downstream systems.
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+ - **Edge Autonomy** for low-connectivity scenarios (manufacturing, maritime, defence).
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+ - **Developer Copilots** confined to internal codebases.
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+
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+ ---
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+
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+ ## Hugging Face Integration
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+
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+ - **Org Repos:** Model cards, adapters, and eval reports published under our Hugging Face organisation for **transparent provenance**.
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+ - **Spaces & Demos:** Private Spaces for stakeholder testing; gated access with audit logs.
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+ - **Artifacts:** Tokenisers, prompt templates, and guardrail grammars for reproducible pipelines.
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+
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+ > Ask us about publishing **redacted eval sets** and **prompt grammars** alongside each model variant.
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+
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+ ---
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+
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+ ## Getting Started
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+
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+ 1. **Choose a deployment:** UK/EU managed cloud, edge appliance, or on-prem.
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+ 2. **Select a model class:** General chat, code, RAG-optimised, or constrained-output.
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+ 3. **Provide domain data (optional):** We prepare adapters or full fine-tunes with strict handling.
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+ 4. **Integrate the API:** Swap your base URL and key; keep your existing SDKs.
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+ 5. **Validate:** Review eval dashboards, latency/cost reports, and guardrail policies.
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+
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+ Contact: **martin@martintech.co.uk**
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+
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+ ---
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+
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+ ## Support & SLAs
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+
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+ - **Production SLAs:** Custom p95 latency, availability targets, and incident response windows.
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+ - **Runbooks:** Operator playbooks for **air-gapped** and **edge** scenarios.
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+ - **Training & Enablement:** Developer workshops, RAG patterns, and prompt-engineering for structured outputs.
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+
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+ ---
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+
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+ ## Why Martin Technologies LTD
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+
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+ - **Sovereignty by design:** Data, runtime, and geography under your control.
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+ - **Open models, no lock-in:** Auditability and long-term portability.
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+ - **Real-time, cost-efficient:** Systems engineering that meets product UX and budget constraints.
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+ - **UK/EU Native:** Residency, procurement, and compliance aligned with your jurisdiction.
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+
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+ ---
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+
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+ ### Legal
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+
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+ © Martin Technologies LTD. All rights reserved.
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+ Data residency options available in the **United Kingdom** and the **European Union**.
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+ Model licences and third-party attributions are documented per-artifact in their respective repositories.