You’ve built a few ChatGPT prototypes. Maybe a RAG demo. But moving to production? Stalled.
You’re not alone. Most enterprises get stuck in “PoC purgatory.” Hallucinations, vendor lock‑in, security fears, spiraling costs.
We’ve solved this – twice.
First, the Intent AI OrchestratorX framework
It’s model‑agnostic – use OpenAI, Claude, Llama, whatever. No lock‑in.
Built‑in RAG and contextual memory – drastically fewer hallucinations.
Deploy cloud, hybrid, or on‑prem – MBSS and VAPT compliant.
OrchestratorX UI – low‑code and full‑code in one place.
Second, the Frost & Sullivan “Systems of Intelligence”
Frost had 60+ years of proprietary research locked in thousands of reports. Analysts were searching manually for hours.
We built a hybrid AI system:
- Cloud OpenAI for generation
- On‑prem embedding models (UAE‑Large‑V1) for data sovereignty
- On‑prem object extraction (cmarkea/detr‑layout‑detection) for parsing tables and charts
Then came the Growth Generator – automated email and proposal creation. A hierarchical recommendation engine (dashboard → module → journey → perspective) that digs bottom‑up.
The game changer: Human‑in‑the‑Loop cost control
Before running expensive LLM tasks, analysts see:
- An interactive checklist of discovered entities (sorted alphabetically)
- A real‑time cost estimator showing projected LLM spend
- A confirmation step before triggering the pipelineA full audit log of their selections
Result: Instead of processing 200 entities (many irrelevant or duplicates), analysts curate down to ~80 relevant ones.
AI query costs drop by 30‑60%. And output quality goes way up.
The numbers
- Proposal generation: from hours to minutes
- AI processing costs: reduced 30‑60%
- Data sovereignty: fully maintained (on‑prem embeddings, cloud generation only where allowed)
Enterprise SLAs: Critical: 15‑min response, 4‑hour resolution
What you can deploy tomorrow
Automated insight generation. Cost‑effective AI operations. 24/7 anomaly detection. A customizable AI Growth Coach with multi‑tenancy and RBAC. And a future‑proof roadmap – model pruning, quantization, hybrid on‑device processing.
Ready to escape PoC purgatory? Let’s pick one use case (intelligent document processing, claims triage, research retrieval) and pilot it with OrchestratorX.
You’ll see production‑ready AI in weeks, not months.