Capability
AI Search Implementation across India
Search that understands intent, across your catalogue, documents and support content, measured on success rate.
- Industries
- 12
- Stack options
- 8
- Typical first release
- 6 weeks
What ai search implementation means when we build it
Orqent Labs rebuilds search around what your logs show is failing, measured on success rate rather than on latency alone.
We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep.
Built by engineers who ship production systems, not by a practice that subcontracts the build. Six weeks to something running in production, not six quarters to a strategy document.
What is included
- Search log analysis to find what currently fails
- Hybrid keyword and semantic retrieval
- Typo tolerance and synonym handling for your vocabulary
- Faceting and filtering that matches how people browse
- Zero-result and abandonment tracking
- Relevance measured against a judged query set
Who this is for
We usually work with e-commerce managers, support leaders, knowledge managers and product owners, the people who own the outcome rather than the tooling decision.
AI Search Implementation by industry
Each sector changes the constraints, regulation, systems of record, and what a wrong answer costs.
- AI Search Implementation for E-commerceconsumer protection e-commerce rules
- AI Search Implementation for Retailconsumer protection rules
- AI Search Implementation for SaaS & TechnologySOC 2
- AI Search Implementation for Media & Entertainmentcopyright law
- AI Search Implementation for Education & EdTechDPDP Act 2023
- AI Search Implementation for Healthcare & HospitalsDPDP Act 2023
- AI Search Implementation for Legal ServicesBar Council rules
- AI Search Implementation for Government & Public SectorDPDP Act 2023
- AI Search Implementation for ManufacturingISO 9001
- AI Search Implementation for Logistics & Supply Chaine-way bill compliance
- AI Search Implementation for Financial ServicesRBI guidelines
- AI Search Implementation for Professional Servicesprofessional body standards
AI Search Implementation, stack options
We pick per workload. Each page states the honest trade-off.
- AI Search Implementation with pgvectordata
- AI Search Implementation with Elasticsearchdata
- AI Search Implementation with Pineconedata
- AI Search Implementation with PostgreSQLdata
- AI Search Implementation with TypeScriptframework
- AI Search Implementation with Pythonframework
- AI Search Implementation with Claudemodel
- AI Search Implementation with OpenAI GPTmodel
Questions we get asked
Will semantic search replace keyword search?
No, hybrid beats either alone. Keyword handles exact codes and names precisely; semantic handles intent and paraphrase. Used together they cover each other's weaknesses.
How do you measure relevance?
A judged query set from your real search logs, scored before and after. That makes improvement a number rather than an opinion.
Can it search across multiple systems?
Yes, federated retrieval across your catalogue, documentation and support content, with permissions respected per source.
Considering ai search implementation?
Tell us the workflow and the constraint. We will tell you honestly whether it is worth building.
Or email bd@dtrasglobal.com · call +91 74118 77878