Test better evidence. #
Ingest evidence, generate a proof-bound Context Pack, then compare model input and answers on your workload.
Developer workload access
Send logs, OpenTelemetry, Docker events, telemetry or awkward JSON. Measure ingest, retrieval and proof-bound Context Packs with your own data.
Send events, search retained history and test mixed structured, semantic and relationship queries.
Single-use trial
No account is required. Jylus creates an isolated one-time tenant, compiles the result, blocks further access immediately, and sends the tenant through the deletion lifecycle.
The response contains source-backed facts, proof IDs, conflicts, missing evidence and the deletion state.
Test AI evidence
Use your own current state, history and documents. Jylus returns a bounded Context Pack with facts, timeline evidence, contradictions, freshness and proof IDs.
/api/v1/analyze with the question your model needs answered.
75.130% Recall@10 · 45.663% MRR@10
31.473% program accuracy · zero model calls
TEMPO · FULL LIVE API COHORT The complete test loop
The response keeps facts, temporal evidence, contradictions, missing evidence and proof IDs explicit. Efficiency values are measured from your own request.
curl https://api.jylus.ai/api/v1/analyze \
--request POST \
--header "Authorization: Bearer $JYLUS_READ_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"source": "current",
"text": "What is the latest latency reported by edge-17?",
"vector": {
"text": "latest edge device response time"
},
"context": {
"mode": "decision",
"token_budget": 2000,
"max_facts": 18,
"max_timeline": 12,
"include_documents": false
},
"scan_limit": 1000,
"limit": 24,
"include_results": false
}'
{
"success": true,
"complete": true,
"execution_mode": "native_current",
"context": {
"decision_context_id": "ctx_...",
"decision_readiness": {
"status": "ready",
"can_answer": true
},
"facts": [
{
"statement": "edge-17 reported 12.4 ms latency",
"proof_ids": ["evt_001"]
}
],
"timeline": [
{ "observed_at": "2026-08-21T08:00:00Z", "proof_ids": ["evt_001"] }
],
"contradictions": [],
"missing_evidence": [],
"context_efficiency": {
"source_tokens_estimated": 1842,
"retained_evidence_tokens_estimated": 436,
"estimated_token_reduction_percent": 76.33
},
"proof": { "event_ids": ["evt_..."], "complete": true }
}
}
Test the data engine
curl https://api.jylus.ai/api/v1/events \
-H "Authorization: Bearer $JYLUS_API_KEY" \
-H "Idempotency-Key: try_evt_001" \
-H "Content-Type: application/json" \
-d '{
"stream": "my-workload",
"events": [{
"id": "evt_001",
"type": "telemetry.sample",
"occurred_at": "2026-08-21T08:00:00Z",
"data": { "device": "edge-17", "latency_ms": 12.4 }
}]
}'