Programmable. Cross-lingual. Audit-ready.
The first embedding API where every AI decision is auditable — built for banks, insurers, hospitals, and governments. Apply named actions to any query in any of 40+ languages, get back a shifted embedding and a signed receipt for every call.
Swahili, Korean, Amharic — three unrelated language families (Bantu, Koreanic, Semitic) across three scripts (Latin, Hangul, Ge’ez). From a 15M model that only saw Zulu.
CPU inference. No GPU, no cloud round-trip. Runs on a $50 phone. Your data never leaves the device.
Sentiment, negation, intent — composable transforms that transfer across languages. Every call signed, reversible, auditable.
The three inversions
A new class of AI.
Three bets the industry got wrong. Three results that change the valuation of every model trained under the old assumptions.
Capability isn't scale.
15M parameters beats InkubaLM-422M on Swahili intent and ties GPT-4o — from a model trained on one language in one epoch on a laptop.
See Swahili head-to-headTrain structure once. Every language inherits it.
Zulu → Korean (61.7%). Zulu → Japanese (56.5%). Zulu → Hindi (60.3%). Zulu → Amharic (60.9%). No parallel data. No target-language training.
See cross-family matrixPrompts are blunt. Operators are algebra.
Name them. Compose them. Sign them. Reverse them. Nine independent claims in the provisional filing protect the controllable-embedding API as a product.
See the API specOne call. A signed receipt.
Steer any embedding with a named action — shift sentiment, remove bias, redirect intent — then read a cryptographic record of exactly what was applied. No retraining. No prompt engineering. Every intervention reversible.
curl https://api.bhala.ai/v1/embeddings/shift \
-H "Authorization: Bearer $BHALA_KEY" \
-H "Content-Type: application/json" \
-d '{
"text": "I want to cancel my subscription",
"lang": "en",
"operators": [
{ "id": "sentiment_positive", "alpha": 1.0 }
]
}'
# → {
# "embedding": [ ... 128 floats ... ],
# "operators_applied": [
# { "id": "sentiment_positive", "alpha": 1.0,
# "shift_norm": 0.431, "latency_ms": 23 }
# ],
# "model": "sci-v3",
# "audit_id": "aud_01HXX..."
# }