SocialIntel Analyzer
One privacy-first platform, four purpose-built modules — Facebook, Instagram, LinkedIn and X — that collect publicly visible social activity and turn it into AI-analyzed, evidence-ready intelligence. Every step runs on infrastructure the organization already owns, so no investigation data, image or finding is ever sent to an outside cloud
What it is
Four specialist assistants, one local brain
Imagine four specialist research assistants — one who knows Facebook inside out, one who knows Instagram, one who knows LinkedIn, and one who knows X (Twitter) — all working on the same desk, using the same notebook, and reporting to the same manager. Each module is deeply specialized in a single platform, but they all share the same underlying brain (a local AI engine), the same private storage, and the same reporting format.
Instead of an investigator manually scrolling through profiles, screenshotting posts, and trying to remember who is connected to whom, each module automates that entire process: it gathers what is publicly visible, reads the tone and sentiment of what people are saying, spots recurring faces or accounts, maps out relationships and networks, scores who matters most, and produces a finished, shareable report — all without any of that information leaving the organization's own computers.
Two experience levels run over the same loop. Normal (Standard) mode takes a single target at a time — one profile, post or search term — at standard collection depth, with automatic AI analysis, dashboard review and one-click report export. Professional / Pro mode adds multi-profile monitoring across several targets in parallel, deeper collection (more posts, full reply threads, commenter profiling) and advanced outputs: threat-pattern flags, evidence dossiers and multi-format export as PDF, CSV, JSON or ZIP.
Four platforms. One local brain. One trustworthy report.
- Facebook, Instagram, LinkedIn and X, each covered by its own dedicated module
4 platforms
Facebook, Instagram, LinkedIn and X, each covered by its own dedicated module
- One collection-to-report loop, the same under every module in both modes
6 stages
One collection-to-report loop, the same under every module in both modes
- Investigation data, images or AI output transmitted to an outside AI provider
0
Investigation data, images or AI output transmitted to an outside AI provider
- Development, Enterprise and Air-Gapped deployment, so setup scales with sensitivity
3 tiers
Development, Enterprise and Air-Gapped deployment, so setup scales with sensitivity
How it works
From target to finished report, entirely on local infrastructure
01
Pick a platform
Facebook, Instagram, LinkedIn or X
02
Authorized session
Log in the way a normal user would
03
Local collection
Posts, photos, profiles and comments gathered
04
Local AI analysis
Sentiment, faces, OCR and location signals
05
Map & score
Relationships, networks, risk / actor scores
06
Dashboard & report
Interactive graph plus PDF / CSV / JSON
Run again for the next profile or search — the same simple loop, every time.
Product exclusiveness
Ranked high to low, most strategically important first
100% local AI processing, zero cloud dependency
No raw data, images or AI output ever leaves the organization's own machines — the single most important differentiator across all four modules.
Flagship capability · nothing sent to an outside AI provider
One suite, four platforms
Facebook, Instagram, LinkedIn and X are each covered by a dedicated, purpose-built module instead of a single shallow multi-platform scraper.
A dedicated module per platform
Platform-specific depth
Each module is built around the real structure of its platform — reply threads on X, resume correlation on LinkedIn, face clustering on Facebook and Instagram — rather than a generic tool stretched to fit.
Reply threads · resume correlation · face clustering
Integrated computer vision
Facial matching and OCR (text-in-image reading) are built in across the visual-heavy modules, removing hours of manual photo review.
Facial matching and OCR across the visual modules
Automated relationship & network mapping
Every module can turn raw activity into an explorable, visual network graph of who is connected to whom.
An explorable network graph, per module
Behavior / actor / risk scoring
Raw activity is converted into a single prioritization score per profile, so analysts know where to look first.
One prioritization score per profile
Evidence-grade, multi-format reporting
Every module produces a polished, shareable PDF/HTML report, with CSV/JSON export available where deeper downstream analysis is needed.
PDF · HTML · CSV · JSON
Flexible, portable deployment
Containerised installation with CPU-or-GPU flexibility and Development / Enterprise / Air-Gapped deployment tiers, so setup scales with sensitivity.
Containerised · CPU or GPU · three deployment tiers
Market research comparison
How the suite compares to the tools it competes with
Keeps all data & AI processing on-premise (no cloud)
- Maltego / Social Links
- Partly — Cloud-dependent features
- Apify / Bright Data / PhantomBuster
- No — No
- SpiderFoot / Lampyre / Recon-ng
- Partly — Partial / optional
- This suite
- Yes — Yes — all 4 modules
Purpose-built per platform (not generic multi-platform)
- Maltego / Social Links
- No — General-purpose, multi-platform
- Apify / Bright Data / PhantomBuster
- No — General-purpose
- SpiderFoot / Lampyre / Recon-ng
- No — General-purpose
- This suite
- Yes — Dedicated module per platform
Facial recognition / image intelligence built in
- Maltego / Social Links
- Partly — Limited / add-on dependent
- Apify / Bright Data / PhantomBuster
- No — No
- SpiderFoot / Lampyre / Recon-ng
- No — No
- This suite
- Yes — Facebook & Instagram modules
Behavior / actor / risk scoring
- Maltego / Social Links
- Partly — Limited
- Apify / Bright Data / PhantomBuster
- No — No
- SpiderFoot / Lampyre / Recon-ng
- No — No
- This suite
- Yes — Yes — all 4 modules
Automated, evidence-grade report generation
- Maltego / Social Links
- Yes — Yes
- Apify / Bright Data / PhantomBuster
- Partly — Export only
- SpiderFoot / Lampyre / Recon-ng
- Yes — Yes
- This suite
- Yes — PDF / HTML / CSV / JSON
Runs a locally-hosted AI model
- Maltego / Social Links
- No — No
- Apify / Bright Data / PhantomBuster
- No — No
- SpiderFoot / Lampyre / Recon-ng
- Partly — Partial
- This suite
- Yes — Yes — all 4 modules
The architecture
Four platform modules — one shared local core
- FacebookIntelligence & Investigation
- InstaScrapeStudio Pro (Instagram)
- SOCMINTLinkedIn Intelligence
- X ScraperStudio (X / Twitter)
Shared local core engine
One brain, four modules
- Local AI (LLM) engine
- Local database
- Container runtime
- Face / OCR / Sentiment models
100% on-premise — zero cloud dependency.
- Unified dashboardNetwork graphs · actor / risk scoring
- Evidence-grade reportPDF · CSV · JSON export
Deployment Strategy
Three tiers — and at none of them does data leave the building
- Building, testing and refining the suite itself — moderate setup effort, one working environment
Development
Building, testing and refining the suite itself — moderate setup effort, one working environment
- Investigation teams running day-to-day casework across multiple analysts, connected to shared local infrastructure
Enterprise
Investigation teams running day-to-day casework across multiple analysts, connected to shared local infrastructure
- Government, defense or highly sensitive environments, which typically choose this tier instead
Air-Gapped
Government, defense or highly sensitive environments, which typically choose this tier instead
Because deployment happens entirely within the organization's own infrastructure across all four modules, IT and security teams retain full control over access, data retention and compliance — with no external vendor account, cloud contract or data-sharing agreement required at any point.
Deployment strategy
The same five setup steps, for all four modules
Prepare the environment
Install the containers and the local AI engine on a server or workstation, or — for the professional-network module — as a browser extension.
Obtain the platform
The IT team downloads the module's software package from its source repository.
Build and start
Each module builds into a ready-to-run container; a standard CPU is enough to start, with optional GPU acceleration for faster AI analysis.
Connect a session
The analyst provides an authorized, logged-in session for the relevant platform — Facebook, Instagram, LinkedIn or X — at the same access level a normal user has.
Launch the dashboard
The team opens the module's web-based control panel in a standard browser, and the system is ready for investigations.
Market position
Where the gap is widest
Measured against the four categories of tool the suite is actually evaluated alongside.
- Against Maltego / Social Links
- These tools trade breadth for depth — they cover many data sources shallowly and rely partly on cloud processing. The suite trades that breadth back for full local processing and platform-specific accuracy.
- Against Apify / Bright Data / PhantomBuster
- These are collection- or automation-first tools that hand back raw data or drive marketing workflows. The suite adds the missing analysis layer — vision intelligence, sentiment, scoring — natively, with nothing sent to an external SaaS platform.
- Against SpiderFoot / Lampyre / Recon-ng
- These are general reconnaissance frameworks with little to no platform-specific capability and minimal built-in AI. The suite offers a purpose-built, automated alternative for each social platform it covers.
- Against Recorded Future / Babel Street
- These are broad, expensive, cloud-based intelligence platforms built for large security organizations. The suite is lighter-weight, locally hosted, and priced around infrastructure the organization already owns rather than per-record or enterprise contracts.
Frequently Asked Questions
No. Across all four modules — Facebook, Instagram, LinkedIn and X — collection, AI analysis and report generation run entirely on infrastructure the organization controls. No investigation data is transmitted to an outside AI provider.
No. Every module only collects information that is publicly visible to an authenticated session — the same content a normal logged-in user could see. None of the modules bypass a platform's privacy settings.
No. Every module runs on a standard CPU. A GPU is supported and will speed up AI processing across the suite, but it is optional rather than required.
Yes. Each module is a self-contained platform and can be deployed independently, though they share the same containerised local-AI deployment pattern, making it straightforward to add the remaining modules later.
Most day-to-day investigation teams land on the Enterprise tier, which connects multiple analysts to shared local infrastructure. Government, defense or highly sensitive environments typically choose the Air-Gapped tier instead.
Depending on the module, findings export as a polished PDF, an HTML report, a CSV spreadsheet, a JSON data file, or a ZIP archive of collected media — chosen to fit whatever workflow the team already uses.
Because every module is deployed entirely inside the organization's own environment, the organization's existing IT security policies, access controls and data retention rules apply directly — there is no third-party cloud provider in the data path.
Because the suite collects and analyzes personal information — including facial data on some modules — its use should be governed by the organization's data protection, privacy and applicable legal review processes before deployment, particularly for investigative use cases involving named individuals.
The modular design — local AI, collection, scoring and reporting used consistently across all four modules — provides a foundation that could be extended to additional public data sources in future releases.
The rest of the line
More in TrustShield OSINT
Four platforms. One local brain. One trustworthy report
Have a solutions engineer walk your team through a collection, the local AI analysis and the report it produces — none of it leaving your own infrastructure.