A leading cultural institution partnered with DeepRails to turn a bold idea into a business win: bring historical figures to life as safe, historically accurate museum guides who could converse with visitors in real time.
The Challenge
Our partner set out to reinvent how people experience history: not by reading plaques, but by conversing with it. Their vision: a lifelike interactive portrait capable of speaking, reasoning, and reacting to visitors in real time. The challenge was turning that vision into a museum-ready experience that could demonstrate the future of interactive exhibits while maintaining absolute historical and factual integrity.
To attract major U.S. cultural institutions, the team needed a system that could deliver an emotionally powerful, "living history" experience without risking factual drift or hallucinations. They turned to DeepRails to architect and build the core AI safety layer, ensuring every response reflected an authentic historical worldview.
- Responses had to be historically faithful to the figure's voice, beliefs, and worldview.
- The installation needed to ensure safety and trust, avoiding hallucinations or inappropriate answers.
- Museum operators required observability: a clear window into every interaction to ensure quality control and compliance.
The Approach
The DeepRails team proposed embedding its Defend API as the real-time correction layer powering the experience. Every response would be evaluated for correctness, completeness, adherence, and safety before ever reaching the visitor.
The solution also included DeepRails' Hallucination Safe™ certification: a visible badge affixed to the display itself, providing visitors with scannable proof that the interaction was certified safe, accurate, and complete.
A safety badge visitors could see and scan
Every screen carried DeepRails' Hallucination Safe™ certification. Each response was validated for historical accuracy, completeness, and safety before it reached a visitor, and the badge gave the institution and its guests scannable proof that the experience was certified, not just claimed.
The DeepRails Integration
- Authentic persona guardrails: The historical figure's voice, tone, and worldview were constrained to remain rooted in their authentic time period.
- Real-time evaluation: Each generated response passed through the DeepRails Defend API for multi-guardrail scoring. Unsafe or incomplete answers were blocked, regenerated, and only then delivered to the display.
- Observability: DeepRails Monitor logged every interaction, providing curators with transparency and audit-ready data.
The Rollout
The system was deployed directly into a museum environment, with visitors able to walk up to the display, ask questions, and hear replies in a period-accurate voice. Every screen carried a Hallucination Safe™ sticker, giving visitors a scannable way to verify the safety credentials of the installation.
The Results
- First-of-its-kind exhibit: A physical GenAI installation where visitors could have a direct, safe conversation with a historical figure.
- Certified safe interactions: 100% of outputs passed guardrails for accuracy, completeness, and safety.
- Visitor engagement: Long dwell times and repeat interactions demonstrated the exhibit's magnetic appeal.
- Operational visibility: Museum staff had full observability, with logs and monitoring ensuring confidence at scale.
Why It Worked
- Physical implementation of GenAI: Moving beyond apps and websites, this project showed how generative AI could inhabit museum spaces.
- Built-in trust: The Hallucination Safe™ certification was more than branding. It visibly reassured visitors that every response was safe.
- Evaluation-first design: Guardrails weren't an afterthought. They were the backbone, ensuring each interaction was historically faithful and museum-grade.
Powered by DeepRails Defend, Hallucination Safe certification, and DeepRails Monitor, this project transformed generative AI into a high‑impact, in‑gallery experience: measurable engagement, bulletproof safety, and operational control.