gopherlabs.ai
SOC 2 Type II · HIPAA · GDPR

Turn your messy data into AI-ready intelligence

Gopherlabs is the data engineering layer for enterprise AI. We clean, structure, and serve your data so RAG pipelines and LLM applications ship with retrieval accuracy you can prove.

Trusted across the modern data & AI stack

Pinecone
Weaviate
Snowflake
Databricks
OpenAI
Anthropic
AWS
What we do

Four primitives. One pipeline.

Every Gopherlabs engagement composes the same four moves — tuned to your data, your domain, and your retrieval goals.

Clean

Deduplicate, normalize, and validate across silos. Schema drift handled, PII redacted at ingestion.

Structure

Chunking, metadata, and ontology-aware enrichment tuned to how your domain actually retrieves information.

Embed

Model-agnostic embeddings with continuous re-indexing as your source data evolves.

Retrieve

Hybrid search, reranking, and evals built in. Measurable accuracy, not vibes.

How it works

A repeatable path from raw data to production AI

Most teams stall between cleaning and evaluating. We've built the operating model that doesn't.

  1. 01Assess

    Audit your sources, schemas, and retrieval quality. Deliverable: a sharp gap analysis.

  2. 02Clean

    Dedup, normalize, redact PII, and resolve entities across systems of record.

  3. 03Build Pipeline

    Ingestion, chunking, embedding, indexing — orchestrated and version-controlled.

  4. 04Evaluate

    Golden datasets, retrieval metrics, hallucination scoring. Ship with evidence.

  5. 05Operate

    Monitoring, drift detection, and managed re-indexing. We stay on the pager.

Services

Engagements built for production

Pick a service or compose them into a full data-to-LLM program.

Data Assessment

Map your data surface area and find the wins before writing a line of code.

Structured Cleanup

Warehouse-grade dedupe, normalization, and lineage for tabular sources.

Unstructured Processing

PDFs, transcripts, tickets, contracts — turned into retrievable knowledge.

RAG Pipeline Engineering

Ingestion, chunking, hybrid search, reranking, evals. End-to-end.

Governance & Compliance

PII redaction, ACLs, audit trails, and data lineage on by default.

Managed LLM Ops

Monitoring, evals, model swaps, and re-indexing as a service.

Industries

Domain knowledge baked into the pipeline

From regulated finance to clinical workflows — we ship with the controls your auditors expect.

Retrieval accuracy lift
10×
Hallucination rate
<2%
PII-safe by default
100%
Pipeline uptime SLA
99.9%
Gopherlabs took six years of fragmented PDFs and turned them into a retrieval layer our analysts actually trust. Hallucinations dropped to near-zero.
Priya Natarajan
Chief Data Officer, Meridian Financial

Ready to make your data AI-ready?

Book a 30-minute assessment. We'll map your stack, your bottlenecks, and the fastest path to production-grade retrieval.