Triage a 21-language crisis stream before an analyst reads a word.
News wires, social streams, and field reports arrive faster than any analyst team can read them. This architecture inserts the Crisis Intelligence analyzer as a triage layer - every item arrives at the workbench already tagged with displacement, conflict, humanitarian, and governance signals.
Illustrative reference architecture. The scenario, volumes, and economics below are modeled - not a named customer case study. Validate every number against your own workload.
The scenario
A risk-intelligence provider monitors public feeds across Eastern Europe, the Middle East, and East Africa for humanitarian and security clients. The stream mixes Ukrainian, Russian, Turkish, English, and a dozen other languages. Today, keyword filters over-fire and analysts still read most of what survives - the genuinely important displacement and escalation reports surface whenever the queue happens to reach them.
Before / after architecture
Before
With Sentiqra
Decision ownership stays with you
- Sentiqra produces indicators. Your alerting rules, escalation thresholds, and client-facing language stay in your pipeline.
- The same text analyzed six months apart returns the same signal set - configuration ID and fingerprint travel with every item.
- Analyst attention is the scarce resource this architecture protects - the analyzer triages, analysts interpret.
Illustrative economics
Both columns are modeled from explicit assumptions. Do not treat these as guaranteed savings - model them against your own workload.
Current approach (modeled)
- Analyst-minutes per item x items/day x loaded analyst cost
- + missed-event cost when escalation reports wait behind noise
- + multilingual coverage gaps where keyword lists do not exist
With Sentiqra (modeled)
- N items/day x 1 Crisis Intelligence run per item
- = N analyzer runs/day at current Sentiqra pricing
- Analyst time concentrates on high-signal clusters, not the raw stream
Model with your real feed volume. The win is analyst-hours moved from reading to interpreting - and coverage in languages your keyword lists never had. See current pricing.
Failure behavior
Enterprise architects care about what happens when analysis is unavailable almost as much as accuracy. Define these states explicitly.
Sentiqra available
Normal flow - every item arrives tagged with indicator groups and confidence scores.
Analyzer latency spike
Items buffer in your ingest queue and process async - ordering may lag, nothing is dropped.
Sentiqra unavailable
Fallback to the existing keyword-filter path. Defined in your runbook - degraded coverage, not a dead pipeline.
Quota / spend cap reached
Explicit operational state. You can shed low-priority feeds first while high-value sources keep running.
Upstream feed failure
No items to analyze - Sentiqra state is unaffected; tagged backlog replays idempotently per request ID.
Illustrative operational impact
One taxonomy across 21 languages
A displacement report in Ukrainian and a border-control item in Turkish land in the same analysis groups - correlation across languages becomes mechanical.
Signal clusters replace the firehose
Analysts open a prioritized workbench grouped by indicator family - displacement, conflict, humanitarian access - instead of a chronological stream.
Replayable evidence for clients
When a client asks why an alert fired, the analysis replays identically - configuration ID, fingerprint, indicator set.
What to measure in your evaluation
Run both approaches against the same labeled production sample. Compare:
The right migration decision should come from your workload - not a generic savings percentage.
Build the reference architecture
Start with 5,000 free analyzer runs and evaluate Sentiqra against your current pipeline.
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