Trust infrastructure for employee emotional data
Your HR AI processes employee sentiment, feedback, and emotional context. Regulators, boards, and employees will ask how. DeepaData gives you evidence-grade artifacts that prove policy-bound processing.
Building employee feedback tools, engagement surveys, or sentiment analysis that processes emotional context from employee communications.
Deploying AI assistants, coaching tools, or wellbeing platforms that handle sensitive employee expressions in workplace settings.
For workplace and HR AI, start with Safety. EU AI Act Article 14 requires human oversight of high-risk AI. Safety attestation gives your compliance team auditable proof that every interaction was checked.
Your first API call
curl -X POST https://www.deepadata.com/api/v1/esaa/evaluate \
-H "Authorization: Bearer dda_live_YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{
"interaction": {
"user_input": "I am feeling overwhelmed by my workload...",
"model_response": "I understand. Let me help you prioritize..."
},
"platform_id": "my-hr-platform"
}'Then add Observe for ongoing monitoring. Add Govern for full artifact governance with W3C Data Integrity Proofs.
Interpret. Seal. Govern. Share. Verify.
EDM.json — Extract what was significant
.ddna — Signed by DeepaData
Metadata — Compliance in-band
VitaPass — Moves with the subject
API — Confirm authenticity
When your HR AI processes emotional context, questions will come. Without artifacts, you have no evidence.
You have logs, not evidence. No artifact shows what emotional context was processed or under what policy.
HR AI influenced a review or recommendation. What did it interpret? Under what consent? You can't prove it.
No documentation of interpretation boundaries. No evidence of policy-bound processing. Just trust us.
EU AI Act requires transparency for high-risk systems. Your emotional data processing has no auditable record.
EU AI Act creates explicit prohibitions and high-risk classifications for workplace AI. Know your exposure before regulators define it for you.
Inferring emotions from biometric signals in workplace contexts is explicitly restricted.
Using AI to assess personality traits that predict job performance.
AI systems that evaluate candidates or monitor employee performance require documentation.
The only trust infrastructure designed for emotional data governance. Interpretation not inference. Artifacts not logs.
DeepaData structures what employees explicitly express in text and transcription. It does not detect hidden emotional states from behavioral signals. This distinction may be relevant in regulatory review.
Every interaction produces a .ddna artifact with full provenance: what was expressed, what was interpreted, what policy applied, when it was issued.
Tamper-evident records using eddsa-jcs-2022. Anyone can verify an artifact hasn't been modified since issuance. Evidence-grade by design.
Consent, jurisdiction, and retention travel with every artifact. Policy enforcement happens at the data layer, not in application logic.
A governance layer between your HR AI and your records. Every emotional context interpretation documented and auditable.
Therapy / Journaling / AI App
.ddna artifacts with W3C Data Integrity Proofs
Compliance
EU AI Act
Litigation
Evidence
Insight
Context
Portability
GDPR
Move from reactive compliance to proactive governance. Every emotional data interaction produces an artifact you can point to.
EU AI Act restricts emotion "recognition" and "inference" in workplace contexts. DeepaData uses interpretation — structuring what employees explicitly express.
Enterprise pricing available. Dedicated support, custom SLAs, and compliance reporting.