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  • Post last modified:December 2, 2025
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Inside Nigeria’s bet on real‑time AI to authenticate online content

What Changed and Why It Matters

Nigeria just put a stake in the ground on AI trust. A Nigeria-led startup, MYai Robotics, launched Curation AI — a real-time engine that verifies digital content and tracks public opinion.

The claim is bold: authenticate news, images, video, audio, and social posts in seconds. It also maps sentiment at scale. That combination targets the core problem AI created: cheap fakes and instant virality.

Why now? Deepfake scams are rising. Government and media workflows are strained. Marketers demand real-time precision. And Nigeria’s public sector is testing AI for misinformation control and local-language access.

Here’s the signal: real-time AI is moving from search and ads into authenticity and governance. Trust is becoming product strategy.

“World’s first real-time content authentication and opinion-intelligence engine.”

The Actual Move

MYai Robotics unveiled Curation AI across Nigerian tech media and social. The product pitch is consistent across reports:

  • Real-time verification of text, images, video, audio, and social posts
  • Detection of manipulated or misleading media within seconds
  • Opinion-intelligence: monitoring public sentiment on topics in real time
  • A Nigeria-led team, with entrepreneur Kayode Aladesuyi linked to the effort

“Verifies news, images, videos, audio and social posts within seconds.”

Unlike static LLM tools, Curation AI says it operates on live internet data. Coverage positions it for newsrooms, brands, public agencies, and platforms that need trustworthy classification at speed.

This sits within a broader national backdrop. Nigeria is piloting AI tools to fight fake news and serve local languages. The CAC’s earlier attempt at AI-driven instant company registration shows both the ambition and the risks of deploying real-time AI in public services. Meanwhile, marketers are leaning into real-time precision, and security experts warn that AI scams are getting better and faster.

“The tool uses real-time internet data to give accurate and timely responses.”

The Why Behind the Move

Zoom out and the pattern becomes obvious: authenticity is the next real-time AI market.

• Model

Real-time retrieval + multimodal forensics + claim matching. Speed and recency over static knowledge. Expect heavy use of metadata checks, cross-source corroboration, and anomaly detection.

• Traction

Strong local media coverage and ecosystem interest. No disclosed customer logos or metrics yet.

• Valuation / Funding

No public funding details reported. Early narrative suggests a product-led, enterprise-first motion.

• Distribution

B2B integrations into newsroom CMS, agency tooling, government workflows, and platform safety stacks. APIs and dashboards will matter more than a consumer app.

• Partnerships & Ecosystem Fit

Fact-checkers, media consortia, and safety teams are natural partners. Local-language coverage in Nigeria is a differentiator. Alignment with standards like C2PA will be key.

• Timing

2025 is a deepfake year. Elections, brand safety, and crisis response raise the cost of being wrong. Real-time beats batch review when decisions must be made in minutes.

• Competitive Dynamics

Global players exist in provenance and safety. Few combine real-time, multimodal verification with opinion-intelligence as a single engine — especially from Africa. Local trust and data access can compound into a moat.

• Strategic Risks

False positives/negatives erode credibility fast. Data access and platform ToS limits may bottleneck coverage. “World’s first” claims invite scrutiny. Costs of real-time crawling, evaluation transparency, and regulatory exposure must be managed.

Here’s the part most people miss: the moat isn’t the model — it’s operational trust at speed.

What Builders Should Notice

  • Real-time is a product decision, not a feature. It reshapes architecture and cost.
  • Trust compounds. Publish evaluations, error bars, and audit trails early.
  • Multimodal beats single-channel. Attacks don’t stick to one format.
  • Distribution lives in workflows. Win with APIs, integrations, and standards.
  • Local-language coverage is a wedge. It unlocks underserved trust gaps.

Buildloop reflection

In AI, speed without trust is noise. Trust at speed is a moat.

Sources

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