AI SEARCH
Search that understands what people mean.
Keyword search returns documents that contain the words. AI search returns the answer. We build semantic and hybrid search — relevance-tuned and grounded — for products, support, and internal knowledge.
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Enterprise-grade delivery. Human-verified outcomes.
Built for teams that can't afford to guess.
Keyword search returns documents that contain the words. AI search returns the answer. We build semantic and hybrid search — relevance-tuned and grounded — for products, support, and internal knowledge.
Modern users expect search to behave like an answer engine. When it returns a wall of weak keyword matches, they bounce.
The fix is rarely 'add AI' — it's combining semantic understanding with the precision of lexical search, then reranking the results and, where it helps, generating a direct grounded answer. We tune relevance against your real queries instead of trusting defaults.
How we build search that converts.
Query understanding
Spelling, synonyms, intent classification, and query rewriting so 'cheap flights ny' works.
Hybrid retrieval
Dense embeddings for meaning + BM 25 for exact terms, fused for the best of both.
Reranking
A cross-encoder reorders the top results — the single biggest precision lever.
Answer generation
Optional: a grounded, cited answer above the results for question-style queries.
Relevance tuning
We build a judgment set from your real queries and measure NDCG, not vibes.
Speed
Caching, ANN tuning, and payload trimming to hold sub-200 ms at your scale.
Where this shows up.
E-commerce search
Intent-aware product discovery that lifts conversion and surfaces the long tail.
Help center / deflection
Answer the question before it becomes a ticket.
Documentation search
Developers find the right page and snippet, fast.
Enterprise search
One search box across wikis, drives, and tickets — with permissions respected.
Content & archive search
Semantic search over articles, transcripts, and media metadata.
Structured + unstructured
Search that spans both your database and your documents.
Ways to engage.
Relevance evaluation of current search
Judgment-set + NDCG baseline
Prioritized improvement plan
Hybrid retrieval + reranking
Query understanding
Relevance tuning + monitoring
30-day support
Relevance iterations on real queries
New content sources
A/B testing support
From a typo to the right answer.
Query understanding, hybrid retrieval, and reranking — the pipeline that turns 'retrn polcy' into the right result.
We measure NDCG against a judgment set built from your real queries — so 'better' is a number, not an opinion.
Often we build on top of what you have.
Elasticsearch or Open Search already handle your lexical search and infrastructure well. We add the semantic layer and reranking on top.
You keep the operational tooling you trust and gain search that understands intent — without a risky migration.
What are people failing to find?
Send us a handful of real queries that return bad results. We'll show you why — and what better looks like.
Ready to build?
Let's build your next intelligent platform.
Share your goals — we'll recommend a model, timeline, and team that fits Aanandi Technosoft.
Frequently asked questions
Do we replace Algolia/Elasticsearch?+
Often we build on top of them. Elasticsearch/OpenSearch handle lexical and infra; we add the semantic layer and reranking. We integrate rather than rip-and-replace where it makes sense.
How do you measure 'better'?+
A judgment set from your real queries plus NDCG/precision@k, measured before and after — and ideally an online A/B test on conversion or deflection.
Will it be fast enough?+
Yes. We design for your latency target with caching and tuned ANN, and reranking only the top candidates.
Can it answer, not just list?+
Yes — grounded answer generation with citations for question-style queries, alongside the ranked results.