How It Works
We map your enterprise data sources — Cloud Storage, BigQuery, SharePoint, Drive — define the chunking strategy, plan the Vertex AI Search index structure, and document access controls before any data moves.
We set up Vertex AI Search datastores, configure Gemini grounding integration, tune hybrid search parameters, and ingest your documents — iterating on retrieval quality with test queries before production.
We benchmark retrieval accuracy against your ground-truth query set, deploy to production with latency SLAs, and wire up freshness automation so your search index stays current as documents change.
What's Included
End-to-end setup of Vertex AI Search datastores across your document corpus — structured and unstructured data — with embedding generation, indexing, and namespace configuration handled by our team.
Configure and tune hybrid search — combining dense vector similarity with sparse keyword matching — to maximise retrieval accuracy across diverse query types and document formats.
Use Google Cloud Document AI to extract structured content from PDFs, scanned documents, and forms before indexing — dramatically improving retrieval accuracy over unprocessed binary files.
Build RAG pipelines that retrieve context directly from BigQuery — enabling Gemini agents to ground responses in structured analytical data, metrics, and real-time query results.
Implement IAM-aware search so agents only retrieve documents the authenticated user is permitted to see — enforcing the same access controls your existing GCP data governance policies require.
Wire Vertex AI Search into Gemini via the Grounding API — ensuring every agent response is grounded in retrieved, cited documents rather than model-generated hallucinations.
Who It's For
Engineering teams building internal Q&A agents, policy assistants, or knowledge workers over large document corpora — you need a production RAG pipeline that returns accurate, cited answers.
Teams migrating from Elasticsearch or keyword-based internal search to semantic, vector-powered search — you need the retrieval accuracy and GCP integration that Vertex AI Search provides.
Organisations with data residency requirements or compliance mandates — you need a RAG system where all data stays within GCP's VPC Service Controls perimeter, with full IAM governance.