Overview
Ask SolE is a reference AI solution expert developed internally at 7Unit to validate how organizations can design, control, and deploy AI systems responsibly in production environments.
Context and constraints
With the rise of tools like ChatGPT and Gemini, organizations recognized that raw AI capability alone was not enough. They needed AI systems aligned with business intent, brand voice, compliance boundaries, and predictable operating costs.
How we approached it
Designed and engineered a modular AI solution expert with strict guardrails, curated knowledge sources, cost controls, and human escalation paths — treating AI as a system, not a feature.
What we built
- A backend-first AI service designed as an API, decoupled from any specific UI implementation.
- A guardrail-driven intelligence layer that defines what the AI can and cannot do.
- A curated knowledge retrieval approach to prevent hallucination and uncontrolled responses.
- A quota- and rate-limited execution model to ensure predictable AI usage and cost control.
- Clear escalation paths where the AI defers to human experts instead of guessing.
Key capabilities
- Strict behavioral guardrails aligned with business and compliance expectations.
- Controlled AI responses grounded in approved knowledge sources only.
- Built-in protection against abuse, excessive usage, and cost overruns.
- Modular architecture adaptable for customer support, internal knowledge, or advisory use cases.
- Human-in-the-loop design for sensitive or high-stakes interactions.
Implementation notes
- Designed as a reference implementation rather than a commercial chatbot product.
- Architecture emphasizes separation of concerns between AI reasoning, policy enforcement, and integrations.
- Engineered to be extensible so different organizations can apply the same principles to their own AI systems.
Outcome notes
- Validated a repeatable approach for designing enterprise-ready AI systems.
- Demonstrated that AI success depends more on system design and guardrails than on model choice.
- Established a practical framework that can be customized for client-specific AI initiatives.
Key outcomes
End-to-end
AI guardrail coverage
Built-in
Cost control mechanisms
Production-grade
Deployment readiness
Technologies
FastAPILLM APIsRedisVector SearchJWT