Shubham
Co-founder & CEO
AI LINC
AI LINC delivers AI‑native enterprise platforms that integrate retrieval, embeddings, and model routing as core components, enabling clients to accelerate product development and reduce costs. Leveraging a Microsoft‑inspired engineering rigor with startup‑level speed, the firm has shipped sixteen engagements across four continents, generating over ₹50 crore in client savings with median delivery times of 14.5 weeks.
- Artificial Intelligence
- Enterprise Software
Updated 4 months ago
Funding
Funding rounds are not available yet.
Founders
Product
Problem
Enterprises often struggle to integrate AI capabilities such as retrieval, embeddings, and evaluation into their existing systems, leading to fragmented implementations, long development cycles, and limited business impact.
Solution
AI Linc delivers AI‑native enterprise platforms where core AI functions are built into the architecture from the start, rather than added as afterthoughts. By applying Microsoft‑level engineering rigor combined with startup‑speed development, the company ships multi‑tenant solutions across continents in a median of 14.5 weeks. Their platforms enforce latency budgets in continuous integration, support vendor‑agnostic model routing, and are priced based on measurable outcomes such as uptime, cost savings, and conversion improvements. This approach reduces time‑to‑value, lowers operational costs, and aligns technology delivery directly with commercial metrics.
Target Audience
Primary customers are large enterprises seeking to embed advanced AI functionality into their products or operations, particularly those requiring rapid deployment and measurable ROI.
Features
- AI‑first architecture with retrieval, embeddings, and evaluation as foundational components
- Vendor‑agnostic model routing for flexible integration of different AI providers
- CI pipelines that enforce latency budgets to ensure performance guarantees
- Multi‑tenant design enabling scalable deployment across global enterprises
- Outcome‑indexed pricing model that ties revenue to client‑measured savings and performance
- High platform uptime (reported near‑100%) across production environments