Skill בחירת ספק AI לארגון ל-Claude

מתי להשתמש

"Choose AI vendor", "Anthropic vs OpenAI", "AI vendor evaluation".

הוראות עבודה

1. Vendor Categories

Foundation Model Providers

• Anthropic (Claude).
• OpenAI (GPT, DALL-E, Whisper).
• Google (Gemini).
• Meta (Llama — open source).
• Mistral — European, open.
• Cohere — multilingual focus.

Specialized AI Tools

• Perplexity — search.
• Midjourney — images.
• ElevenLabs — voice.
• Runway — video.

Embedded AI

• Microsoft Copilot — Office.
• Notion AI — docs.
• GitHub Copilot — code.

Cloud AI Platforms

• AWS Bedrock — multi-model.
• Google Vertex — Google models + others.
• Azure OpenAI — enterprise OpenAI.

2. Selection Criteria

א. Capability Match

• Does it solve your use case?
• Test with real data.

ב. Quality

• Benchmark against alternatives.
• Hebrew quality (if relevant).

ג. Cost

• Per-token / per-feature.
• Scale considerations.
• Hidden costs.

ד. Latency

• Real-time needs.
• Throughput.

ה. Privacy

• Data retention policy.
• Training opt-out.
• Self-host option.

ו. Compliance

• SOC 2 / ISO 27001.
• HIPAA / GDPR-ready.
• DPA available.

ז. Reliability

• Uptime SLA.
• Track record.

ח. Support

• Response time.
• Account manager.

ט. Ecosystem

• Integrations.
• Community.

3. Vendor Lock-in Risk

High Lock-in

• Custom fine-tuned models.
• Vendor-specific APIs (Assistants API).
• Vendor-specific tools.

Low Lock-in

• Standard prompts (portable).
• Open standards (MCP).
• Multi-vendor abstraction (LangChain, OpenRouter).

4. Multi-Vendor Strategy

Why

• Best tool per task.
• Avoid lock-in.
• Fallback if vendor down.
• Negotiation leverage.

How

• Abstraction layer (LangChain, LiteLLM, Portkey).
• Standard prompts.
• Track each vendor.

5. Common Stacks 2026

B2B SaaS Startup

• Claude — main reasoning, content.
• OpenAI — multimodal, voice.
• Pinecone — vectors.
• GitHub Copilot — devs.

eCommerce

• GPT-4o — general AI.
• Klaviyo AI — email.
• Midjourney — product images.

Enterprise

• Anthropic via Bedrock — primary.
• Azure OpenAI — secondary.
• Self-hosted Llama — sensitive.

Privacy-First

• Self-hosted Llama / Mistral.
• Local Ollama.
• Anthropic with DPA.

6. Foundation Model Comparison 2026

7. Evaluation Process

1. Define criteria (use cases + must-haves).
2. Shortlist 2-3 vendors.
3. Free trial / POC each.
4. Build same use case in each.
5. Compare:
   - Quality on test set
   - Cost at projected volume
   - Developer experience
   - Support responsiveness
6. Decide + Plan migration if needed.

8. Negotiation

When

• Annual commitment.
• Volume commitment.
• At renewal.

Levers

• Volume discount — 10-30%.
• Multi-year — 5-15% additional.
• POC commitment — sometimes free.
• Reference customer — discount in exchange.
• Competitive bid — if multiple vendors.

9. Switching Costs

• Prompts may need rewriting (subtle differences).
• Fine-tunes don't transfer.
• Tool integrations — varies.
• Skills in team — Claude vs GPT-4 differences.

10. Israel Specifics

• Local resellers for OpenAI (some).
• Anthropic direct in Israel.
• Israeli AI startups — local options.

11. Common Pitfalls

❌ Single vendor for everything — lock-in. ❌ Marketing-driven decision (not POC-driven). ❌ Latest = best assumption — not always. ❌ Ignoring privacy until breach. ❌ No fallback — vendor outage = downtime.

12. אסיים בהמלצה.

פרומפט לדוגמה

SaaS B2B Israel. Foundation model — choose.

Avoid OpenAI lock-in. Strategy.

Negotiate Anthropic enterprise contract. Tactics.

© 2026 AI Expert Pro | גרסה 1.0.0