Blura SAGA platform
From millions of digital signals to intelligence you can act on.
SAGA continuously monitors public digital signals, understands what is being said, detects emerging threats and narratives, and turns them into structured intelligence for faster, more informed decisions.
How SAGA thinks
The internet is full of signals. SAGA finds the ones that matter.
Conversations, news, narratives, grievances, emerging threats and coordinated activity appear across digital channels every day. SAGA brings these signals together, understands their context and transforms them into intelligence that can be investigated, monitored and acted upon.
01
Digital signals
What enters SAGA
- Social mediaPublic posts, accounts, replies
- News and mediaNews, RSS, articles
- Online communitiesForums, groups, discussions
- GrievancesCitizen inputs and open sources
02
AI understanding
How SAGA makes sense of it
- Language identificationMulti-lingual NLP
- Sentiment analysisTone, emotion and intent
- Entity detectionPeople, organisations, places
- Media analysisImages, video, deepfake detection
03
Intelligence
What SAGA discovers
- ThreatsRisks, incitement, harmful content
- NarrativesEmerging themes and stories
- NetworksConnected accounts and influence
- TrendsShifts over time and by location
04
Action
What teams receive
- Real-time alertsIssues requiring attention
- Intelligence reportsAnalytical and executive summaries
- EvidenceTimestamped, auditable records
- ResponseFor investigation, monitoring or action
Coverage is configurable
Platforms, languages and sources are configured to the operational requirement of each deployment.
Learn moreIntelligence layers
See beyond the signal.
Five intelligence layers transform the same signal into deeper context. Each layer answers a different question — revealing connections, patterns, risks, and actionable intelligence.
Sentiment and narrative intelligence
Understand what people are saying.
Analyze sentiment, tone, and emerging narratives across digital conversations. BLURA SAGA identifies recurring themes, detects shifts in sentiment, and connects related narratives to reveal what is changing, where it is changing, and why it matters.
Learn more about sentiment and narrative intelligence
Threat and escalation intelligence
Detect and prioritise emerging risks.
Identify emerging threats, harmful narratives, and suspicious activity as they develop. BLURA SAGA analyzes threat signals, measures their velocity and reach, and prioritizes risks based on their potential for escalation, helping teams focus on what requires attention first.
Learn more about threat and escalation intelligence
Coordinated campaign and network intelligence
See the connections behind the narrative.
Map the relationships between accounts, content, and narratives to uncover coordinated activity and influence. BLURA SAGA connects related entities and patterns across digital sources, helping investigators understand how narratives spread, who is connected, and where influence is emerging.
Learn more about coordinated campaign and network intelligence
Geo-spatial intelligence
Know where activity is emerging.
Understand where digital activity is emerging and how it is spreading. BLURA SAGA transforms signals into geographic intelligence, revealing hotspots, emerging patterns, and areas that require closer attention.
Learn more about geo-spatial intelligence
Evidence and intelligence outputs
Turn analysis into actionable intelligence.
Turn complex intelligence into clear, defensible outputs. BLURA SAGA generates structured alerts, analytical reports, and evidence packages with the context and source information needed to support investigation, review, and action.
Learn more about evidence and intelligence outputs
The sequence
From signal to intelligence.
BLURA SAGA transforms raw digital signals into actionable intelligence through a connected sequence of detection, analysis, correlation, risk assessment, and response. Every insight remains traceable to its underlying source and context.
01
Detect
Identify relevant signals. Digital signals are continuously collected and filtered to surface activity relevant to your intelligence requirements.
02
Understand
Add context and meaning. AI analyzes language, sentiment, entities, and media to understand what each signal represents.
03
Connect
Reveal relationships and patterns. Related accounts, content, narratives, locations, and events are connected to uncover hidden networks and coordinated activity.
04
Predict
Identify emerging risks. Patterns, velocity, reach, and other intelligence indicators help identify developing threats and areas requiring attention.
05
Act
Turn intelligence into action. Alerts, reports, and evidence packages give teams the intelligence they need to investigate, respond, and make informed decisions.
The record
SAGA does not just monitor content. It connects the context around it.
A post on its own is just a signal. Add its account history, location, narrative, timing, and connected entities — and it becomes intelligence. SAGA brings that context together to reveal the bigger picture.
- Time & SequenceWhen it happened, what was happening around it.
- MediaImages, video, and other digital content.
- OrganizationLinked entities, networks, and affiliations.
- ThreatRelevant risks, indicators, and past incidents.
- SentimentTone, emotion, and how it shifts.
DigitalSignal
- AccountAccount history, activity, and associated accounts.
- Person / EntityIdentity, affiliations, and behavioural patterns.
- LocationWhere it originated, moved, and spread.
- NarrativeKey themes, related conversations, and emerging narratives.
- EventRelated events and the broader situation.
Delivery
Intelligence arrives as an alert — not another dashboard to check.
BLURA SAGA delivers timely, actionable alerts when intelligence requires attention. Each alert provides the context behind the signal, helping teams understand what happened, why it matters, and what needs attention next.
Priority tier
Coordinated narrative detected
Multiple signals indicate a connected pattern.
- High Risk
- Risk level
- 87%
- Confidence
- 248
- Signals
- 18
- Accounts
- 6
- Locations
- 3
- Narratives
What the alert contains
- What happenedThe detected activity, with the relevant records and signals behind it.
- Why it mattersThe risk, context, and intelligence indicators behind the assessment.
- WhereThe location and geographic spread of the activity over time.
- WhoThe people, accounts, organizations, and entities connected to the activity.
- What nextRecommended investigation or response actions, with clear ownership.
From alert to actionWith full traceability
In operation
When a signal becomes intelligence.
From a digital signal to a decision-ready intelligence alert, every step is traceable, contextual, and connected.
Digital signal
A public conversation, event or activity enters the system.
Detect
Unusual activity is identified in real time.
Analyse
Narrative, sentiment and key entities are analysed.
Correlate
Related accounts, locations and events are connected.
Score
Risk is assessed with full context and evidence.
Raise intelligence
An alert or intelligence brief is generated and routed.
Human decision
An analyst reviews and decides the next course of action.
SAGA supports the decision — it does not make it.
Security
Built for sensitive intelligence environments.
Security controls are built into every layer of the platform, with access governed by role, scope, and operational requirements.
- Data at rest
- Encrypted while stored using enterprise-grade encryption standards.
- Data in transit
- Encrypted across platform components using secure communication protocols.
- Role-based access
- Granular access controls ensure users can access only the intelligence and features assigned to their role.
- Authentication
- Multi-factor authentication helps protect access to sensitive intelligence and investigations.
- Audit trail
- User activity, searches, exports, and permission changes are recorded for accountability and auditability.
- Deployment
- Flexible deployment options help keep sensitive intelligence within the organization’s designated security boundary.
Questions
Platform questions.
Anything not answered here, a product specialist can take in the demonstration.
Ask a questionWhat happens to an item that matches nothing?
It is not retained. Collection keeps what a watchlist term or a tracked entity caused it to keep; the rest is discarded at the first step rather than stored against a future query.
Can a score be disagreed with?
Yes, and that is the reason scores are attached to records rather than replacing them. Sentiment, risk, velocity and organic-versus-coordinated attribution all keep their inputs available, so an analyst can open the underlying items and reach a different conclusion.
How are duplicate posts handled?
Near-identical reposts are collapsed into one record carrying a count of occurrences and the accounts responsible. Repetition is therefore measurable as repetition, instead of appearing as reach.
What does source credibility weighting actually change?
News and RSS feeds run through the same pipeline as social sources, and each source carries a credibility weight that changes how much an item contributes to a score. The weight applied is shown on the record. Weights are configurable per deployment [pending sign-off: default weighting scheme], because a judgement about a source belongs to the department operating the system.
Can SAGA tell whether coverage followed the conversation, or the other way round?
News items and social conversation about the same subject are correlated, so the ordering question can be answered. That ordering is frequently the difference between an organic story and a placed one.
What happens in an unsupported language?
Items are collected and stored but not scored [pending sign-off: which languages beyond English, Telugu, Hindi and Urdu are supported]. They are neither dropped nor passed through a model that does not read them.
See SAGA in action
See what your digital environment is telling you.
See how SAGA transforms fragmented digital signals into connected, actionable intelligence.