Own your position in the SI era.

See what AI says about you—and what combined intelligence reveals. CoreCaster’s Superintelligence (SI) brings together multiple AI engines, source evidence and strategic analysis to show how narratives, observed bias and competitive gaps shape your position—and what to do next.

Go beyond a single AI answer. Compare what different engines say, the sources they cite and where their narratives agree or diverge. CoreCaster connects that intelligence with your strategy, corrective content and ongoing verification. See the wider picture. Act. Measure what changes.

Built on AI. Moving towards connected superintelligence. CoreCaster’s SI approach brings the wider picture together—so you can act on your strategy.

Discover your SI position

From individual AI answers to connected SI.

Different engines draw on different information and can give different answers about you. CoreCaster connects their observed behaviour, sentiment and cited sources with fact libraries, correction workflows and repeat verification. That is how we turn separate AI responses into actionable SI.

Multi-engine intelligence

Each engine sees you differently. SI connects the picture. Compare how different AI engines describe you, the sentiment they express and the sources they cite. Identify recurring narratives, observed bias and conflicting answers. CoreCaster brings those findings together as SI—so your next action responds to the wider picture, not one engine’s opinion.

Compare like-for-like questions and dates. An API assessment is an observed answer from that interface, not the answer every user will necessarily see.

Evidence and explanation

Follow the sources. Understand the behaviour. Trace the citations returned with an answer and compare them with the facts in your knowledge library. See where information is missing, outdated or contradicted, and distinguish a factual error from a difference in tone. This gives each correction a clear evidence base.

Analysis of returned answers and sources does not reveal an engine’s private training data or hidden reasoning.

Competitive position

Understand how the narrative shapes your position. Compare how engines represent you and relevant competitors across the same questions. Identify differences in visibility, sentiment and supporting evidence, then prioritise the knowledge gaps that matter to your strategy.

AI-derived competitive comparisons are analysis, not an independent market ranking or proof of commercial causation.

Action and activation

Give AI a better knowledge foundation. Use CoreCaster’s training-layer workflow to organise source-backed facts into a reusable knowledge library. Prepare corrections for the gaps found in each engine, review the message and publish through authorised channels. Work with AI to build clearer, better-supported information for retrieval and future responses.

The training layer coordinates facts, submissions and checks; it is not direct control over a third-party model. Provider acknowledgement alone does not prove retraining.

Rescan and verification

Learn from the differences. Verify the change. Repeat the assessment across the engine set and compare answers, citations and sentiment with the earlier record. Use those observations to refine the fact library and the next correction. This feedback loop connects understanding, action and verification within CoreCaster’s SI approach.

Measure changes in fresh responses. A successful submission is not proof of lasting model learning or identical answers across all engines.

The wider ecosystem

CoreCaster is the flagship intelligence platform. AACIS, ASSEMBLE, Music Shield and NARC are specialist products within its wider ecosystem.

CoreCaster is operated by CC Intelligence Bureau Limited — a Tubey Family Office portfolio company.