What is CHAI?
CHAI (Cognitive Hive AI) is Aether's AI architecture. Instead of relying on one large, expensive language model for everything, CHAI orchestrates a team of specialized Small Language Models (SLMs) - each fine-tuned for a specific task.
Why a Hive?
A team of specialists outperforms a generalist. A fine-tuned 7B model often beats GPT-4 at its specialty while costing 99% less. CHAI gives you the best of both worlds: superior results and dramatically lower costs.
AI Specialists
Aether includes a complete set of AI specialists out of the box, each optimized for a specific content task:
Content Writer
Generates high-quality content in various styles and formats. The Content Writer adapts to your brand voice, follows your style guidelines, and creates engaging content for any purpose.
// Generate content with brand voice
let article = await hive.GenerateContent(
content_type: "blog_post",
prompt: "Write about sustainable packaging trends",
context: TaskContext { language: "en", ... }
)
// Rewrite content in a different style
let rewritten = await hive.RewriteContent(
content: article,
style: "casual",
tone: "friendly"
)
Capabilities:
- Blog posts, articles, and long-form content
- Product descriptions and marketing copy
- Headlines and calls-to-action
- Content expansion and compression
- Style and tone adaptation
SEO Optimizer
Automatically optimizes your content for search engines. Generates meta titles, descriptions, and structured data while suggesting improvements to content structure.
// Generate SEO metadata with JSON-LD
let meta = await hive.GenerateSeoMeta(
content: article,
include_schema: true
)
// Returns: { title, description, keywords, json_ld }
Capabilities:
- Meta title and description generation
- Keyword extraction and suggestions
- JSON-LD structured data for rich snippets
- Content structure recommendations
- Readability analysis
Taxonomy & Tagging
Automatically categorizes and tags content using your existing vocabularies. Extracts named entities (people, places, organizations) and suggests new taxonomy terms when content covers novel topics.
// Suggest tags from existing vocabulary
let tags = await hive.AutoTag(
content: article,
vocabulary_id: "topics",
max_tags: 5
)
// Returns: [{ label, confidence, is_new }, ...]
Capabilities:
- Automatic category assignment
- Tag suggestions with confidence scores
- Named entity extraction
- New term suggestions for novel topics
- Consistent categorization across content
Translation
Translates content between languages while preserving meaning, tone, and formatting. Handles cultural adaptations and technical terminology correctly.
// Translate while preserving HTML
let spanish = await hive.TranslateContent(
content: article,
source_lang: "en",
target_lang: "es"
)
Capabilities:
- 50+ language pairs
- HTML/Markdown preservation
- Cultural adaptation
- Technical terminology handling
- RTL language support
Content Moderation
Automatically reviews content for policy compliance. Detects harmful content, assesses audience appropriateness, and flags items for human review.
// Check content against policies
let result = await hive.ModerateContent(
content: user_submission,
policies: Set::from(["hate_speech", "violence", "adult"])
)
// Returns: { approved, flags, confidence, action }
Capabilities:
- Toxicity detection
- Policy compliance checking
- Sentiment analysis
- Audience appropriateness
- Configurable policies
Multi-Provider Support
CHAI supports multiple AI providers, giving you flexibility in model selection and avoiding vendor lock-in:
| Provider | Models | Best For |
|---|---|---|
| Anthropic | Claude Sonnet, Claude Haiku | Content generation, analysis |
| OpenAI | GPT-4, Embeddings | Semantic search, complex reasoning |
| Gemini Pro | Multilingual, long context | |
| Mistral | Mistral Large, Mixtral | European data residency |
| Local | Any GGUF model | Air-gapped, full control |
Cost Efficiency
CHAI uses efficient model selection to minimize costs while maximizing quality. Classification tasks use fast, cheap models (Claude Haiku), while generation tasks use more capable models (Claude Sonnet).
| Task Type | Default Model | Cost per 1K tokens |
|---|---|---|
| Content Generation | Claude Sonnet | $0.003 in / $0.015 out |
| SEO Optimization | Claude Sonnet | $0.003 in / $0.015 out |
| Translation | Claude Sonnet | $0.003 in / $0.015 out |
| Auto-Tagging | Claude Haiku | $0.00025 in / $0.00125 out |
| Moderation | Claude Haiku | $0.00025 in / $0.00125 out |
| Summarization | Claude Haiku | $0.00025 in / $0.00125 out |
| Embeddings | text-embedding-3 | $0.00013 |
Result: 96% Cost Savings
By using the right model for each task - and caching where possible - Aether delivers enterprise AI capabilities at a fraction of the cost of calling GPT-4 for everything.