#16 — AI Features (Phase 9 stub)

Status: 🟡 Adapter ready (Phase 7) · Features wiring deferred to Phase 9 Last updated: 2026-05-14

---

#Architecture (Already Built)

All LLM access via format-based adapters per global no-hardcoded-providers rule. See:

• app/Adapters/Llm/LlmAdapterContract.php — interface
• app/Adapters/Llm/OpenAICompatibleAdapter.php — covers OpenAI/DeepSeek/Groq/Mistral/Together/OpenRouter/xAI/Ollama/LM Studio/vLLM
• app/Adapters/Llm/AnthropicFormatAdapter.php — for native Anthropic API format
• app/Adapters/Llm/LlmAdapterFactory.php — LlmAdapterFactory::active() returns adapter for the active provider

Owner inputs everything via admin UI: base_url, api_key, default_model. Pricing per 1M tokens (optional, for cost tracking).

$llm = LlmAdapterFactory::active();
if (! $llm) {
    // Feature disabled — owner hasn't configured an LLM provider
    return ['error' => 'No LLM provider configured. Set up in Settings → Providers.'];
}

$response = $llm->chat([
    ['role' => 'system', 'content' => 'You are a helpful sales assistant.'],
    ['role' => 'user', 'content' => "Draft a proposal for {$client->company_name} about web design."],
], ['model' => $userPickedModel, 'temperature' => 0.7]);

echo $response->content;

#Features to Build (Phase 9)

#9.A AI Proposal Drafting

Trigger: Proposal create form → "Draft with AI" button Input:

• Lead/Client context (industry, size, prior projects)
• Selected service template (web design, app dev, consulting)
• Tone (formal, friendly, casual)

Process:

1. Build prompt from template (config/ai-prompts/proposal-drafting.php)
2. Call LlmAdapterFactory::active()->chat(...)
3. Stream response into TipTap editor
4. User reviews, edits, finalizes

Per-feature model picker: Owner sets which provider for proposal drafting in Settings → AI. Empty → feature disabled.

#9.B Email Thread Summarization

Trigger: Long ticket thread → "Summarize for me" button on ticket detail Output: Bullet-point summary of issue + actions taken so far

#9.C Smart Lead Scoring

Trigger: Lead create / activity log update Process: LLM scores 1-10 based on company size, industry, expressed urgency, source quality Display: Lead list shows AI score badge

#9.D KB Article Suggestion (Ticket Form)

Trigger: Customer types ticket subject + body Process: Semantic search against published KB articles using embeddings (if embedding endpoint configured) or LLM-based relevance Display: "Maybe this helps?" — suggest top 3 articles before submit

#9.E Auto-Tag Ticket

Trigger: Ticket created Process: LLM classifies into: bug, feature-request, billing, how-to, complaint Display: Auto-set tag, agent can override

#9.F Customer Communication Drafting

Trigger: Ticket reply, follow-up email Process: LLM drafts response based on conversation history + tone preference Display: Editable draft in reply box

#Cost Control

• Per-feature toggle on/off (Settings → AI Features)
• Per-feature provider assignment (different model for different task — owner choice)
• Usage tracking: llm_usage table logs prompt_tokens + completion_tokens per call
• Owner inputs cost_per_1m_input and cost_per_1m_output per provider for spend dashboard
• Monthly budget cap with auto-disable when exceeded (optional)

#Privacy

• Sensitive data (full SSN, bank numbers, credit cards) stripped from prompts via regex pre-processor
• Owner can opt-in/opt-out per data type
• LLM calls logged with redacted prompt (for debugging only, retention 30 days)
• Documentation explicitly states what data goes to LLM provider

#Local-First Option

Configure OpenAICompatibleAdapter with:

• base_url: http://localhost:11434 (Ollama)
• api_key: (empty)
• default_model: llama3.1:8b (or whatever you pulled)

Everything works the same — no data leaves your network.

#Implementation Order (Phase 9)

1. Settings UI for per-feature provider assignment + toggle
2. Usage tracking (llm_usage table + observer)
3. Proposal drafting (simplest, highest visible value)
4. Ticket auto-tag (background, low risk)
5. KB suggestion (requires embedding endpoint OR LLM relevance)
6. Email summarization
7. Lead scoring
8. Communication drafting

Each feature is opt-in — admin sets provider in Settings → AI; if no provider, feature shows "Configure LLM provider to enable" message.

---