Narrative intelligence infrastructure for contested media environments

Who’s informing. Who’s influencing. What signals prove it.

ObstaAI helps organizations track media and social media, detect bias and manipulative framing, measure narrative pressure, and generate response-ready language grounded in identifiable signals.

Built for groups that need more than alerts. ObstaAI turns articles, screenshots, clips, and posts into structured intelligence: frame concentration, repetition rate, narrative velocity, and response vocabulary.

Bias Signal Index
12+
Core framing and manipulation markers surfaced per item.
Frame Concentration
1 feed
See which narrative dominates a source or cycle.
Narrative Velocity
Cross-platform
Track how fast a line of attack is spreading.
Response Readiness
Brief-ready
Move from messy coverage to usable language quickly.
Platform

From raw media flow to structured narrative intelligence

ObstaAI is an intelligence layer for organizations that need to know what is informing, what is influencing, and which signals justify that conclusion.

Ingest

Articles, screenshots, posts, clips, newsletters, transcripts, and internal notes feed into one review layer.

Score

Content is broken into framing signals, influence markers, repetition patterns, and reputational pressure indicators.

Operationalize

Turn analysis into briefings, watchlists, evidence packs, and response language leadership can use.

Signal model

The signals that confirm bias, framing, and manipulative text

The point is not to wave vaguely at “bias.” It is to identify the pattern, show the signal, and give teams language that can hold up under scrutiny.

Signal density

How many framing or influence markers appear in a single item.

Repetition rate

How often a phrase, label, or frame reappears across sources.

Cross-source convergence

Whether multiple outlets or accounts are landing on the same framing pattern.

Narrative pressure

Whether the content is merely reporting, actively framing, or pushing coordinated influence.

Use cases

Built for organizations operating inside hostile or fast-moving information environments

For teams that are publicly judged, narratively pressured, or forced to answer quickly without losing precision.

Special-interest groups Lobbyists Political campaigns Politicians and elected offices Public-affairs teams Issue advocacy organizations Coalitions and trade groups Strategic communications teams

Monitoring

Track whether a line of attack is emerging, accelerating, or consolidating across outlets and social channels.

Briefing

Convert chaotic coverage into clean summaries for leadership, spokespeople, advisors, and principals.

Response prep

Give teams disciplined language for naming slant, selective omission, narrative stacking, or manipulative rhetoric.

Signal flow

A simple intelligence flow from input to response

A cleaner way to show what the platform actually does.

Step 1

Collect

Bring in articles, posts, screenshots, clips, and transcripts tied to a story, issue, person, or attack line.

Step 2

Classify

Sort by topic, source type, probable intent, framing style, and manipulative technique.

Step 3

Score

Surface frame concentration, signal density, repetition rate, and narrative velocity across the set.

Step 4

Brief

Generate response vocabulary, summary notes, and decision-maker briefings your team can use immediately.

Plans and usage

Seat tiers, end-user types, and how pricing maps to capability

In the enterprise model, role controls authority and tier controls capability. That means a workspace can mix seat types: admins, analysts, lighter review seats, and higher-capability users on the same tenant.

Entry seat
Free
Light access
Best for monitoring-only users and light reviewers.
Typical use
  • View selected dashboards
  • Limited data access
  • Light usage and review workflows
Operational seat
Team
Write and collaborate
For active communications teams, research pods, and response operations.
Typical use
  • Data entry and analysis submission
  • Collaboration across a tenant workspace
  • Higher usage and working-level operations
Advanced seat
Enterprise
API and reporting
For advanced users who need broader reporting, deeper access, and integration-heavy workflows.
Typical use
  • Advanced reporting
  • API and integration access
  • Highest-capability enterprise workflows
End-user types

Different users need different seats

The right package is usually a mix, not a single tier for everyone.

End-user type What they need Recommended tier Typical role
Executive / principal Briefs, summaries, and light visibility Free or Pro client_analyst
Research analyst Daily monitoring, history, entity review, exports Pro client_analyst
Communications or war-room operator Run workflows, submit analyses, collaborate, maintain watchlists Team client_analyst
Tenant lead / operations owner User management, settings, oversight, tenant-wide control Enterprise client_admin
Roles and permissions

Roles decide authority. Tiers decide capability.

This keeps pricing clean: you pay for the seat capability users need, while permissions determine who can manage the workspace and who can simply work inside it.

Role Scope Permissions Pricing relationship
client_admin Tenant-wide Manage workspace settings, user access, seat mix, and tenant-level oversight Usually paired with Enterprise seats because admins need the broadest capability
client_analyst Tenant data Run analyses, review content, work in monitoring and briefing flows Can sit on Free, Pro, Team, or Enterprise depending on workload
Internal support roles Platform-level Internal platform admin or support access, not customer-facing seat types Not part of customer pricing
Pricing logic

How enterprise pricing actually works

Pricing should follow the operational shape of the tenant: seat mix, usage intensity, and infrastructure requirements.

1. Workspace base

One tenant workspace gives the organization its own environment, settings, data scope, and branded operating layer.

2. Seat mix

Add the right mix of Free, Pro, Team, and Enterprise seats depending on who only reads, who works, and who administers.

3. Usage and infrastructure

Higher analysis volume, advanced reporting, API usage, custom domains, or isolated infrastructure should push pricing upward.

Response layer

From “something feels off” to language you can actually use

ObstaAI closes the gap between noticing a pattern and naming it clearly.

Example output

  • This coverage uses selective omission to create a distorted impression of motive.
  • This item relies on emotional loading and certainty inflation rather than verified evidence.
  • This narrative shows cross-source repetition of a reputational frame.
  • This article applies asymmetrical scrutiny while leaving comparable counterfacts untouched.
  • This attack line is gaining speed because a simple label is being repeated across multiple channels.

What teams do with it

  • Prepare spokesperson notes and issue briefs
  • Flag hostile framing for legal, policy, or communications review
  • Build evidence-backed response language for internal and external use
  • Track escalation before a narrative hardens into accepted wisdom
  • Create institutional memory around recurring attacks and talking points
Not enterprise?

Individuals and small teams can use the consumer product

ObstaAI is the infrastructure layer for organizations. If you want a lighter self-serve experience for personal use, independent analysis, or small non-enterprise workflows, use the consumer product built on the same core engine.

Best for personal use

  • Analyze headlines, posts, screenshots, and articles one by one
  • Get direct breakdowns of framing, bias, and manipulative techniques
  • Use a simpler self-serve workflow without enterprise setup

Go to CRITIanal

The consumer experience lives at critianal.com. Start there if you want personal access, a lighter workflow, or a non-enterprise entry point.

Why teams use ObstaAI instead of generic monitoring

Category Generic monitoring ObstaAI
What it surfaces Mentions, alerts, volume Mentions plus framing, influence signals, narrative pressure, and response language
Usefulness Basic awareness Awareness, briefing, interpretation, and disciplined response
Output Counts and feeds Counts, rationale, named signals, and reusable briefing language
Institutional memory Fragmented Centralized across narratives, actors, incidents, and response patterns
Request access

Stand up a signal layer your team can actually use

Give your organization a structured way to detect bias, track influence signals, quantify narrative pressure, and respond with evidence-backed language.

Self-serve onboarding, tenant workspaces, and branded enterprise environments can be layered on top of the same core platform.