RAG development for US teams that need answers grounded in their own data.

Honest answer: our Mohali team runs IST, which gives a native two-to-three-hour window with US Eastern late afternoon. For US clients that need full US-business-hours coverage, we run a dedicated US-hours pod out of our Frisco, TX office and a tech-lead-on-call rotation covering 9am to 6pm Central — not a junior support shift, the same senior engineers building your RAG system. Twice-weekly demos run in US business hours; written updates land before your standup. If your engagement genuinely cannot survive without same-zone synchronous coverage at all hours, we will say so on the first call so you can pick a US-only consultancy instead.

Because vector similarity misses on rare entities, identifiers, and exact phrases — the cases where BM25 lexical recall is undefeated. A drug name, a contract clause number, an error code, a CPT code: dense embeddings collapse these into nearby semantic neighbors and the retriever returns the wrong chunk. We run BM25 (Elastic or Postgres full-text) and dense retrieval (pgvector, Qdrant, or Weaviate) in parallel, fuse the rankings via reciprocal rank fusion, and rerank with a cross-encoder when the eval bar demands it. On the documented medical-inquiry deployment, hybrid lifted citation accuracy from 91% (vectors-only baseline) to 98.4% in production — without that lift, the system would not have cleared the clinical review board.

Citations are not requested in the prompt — they are enforced at the answer layer. Every claim in the model's output is mapped back to a retrieved chunk; claims that cannot be mapped are stripped, and if the strip leaves the answer empty, the refusal layer fires. The chunk IDs in the answer are validated against the actual retrieval set for that turn, so the model cannot fabricate a citation pointing at a chunk it never received. Confidence scoring on every answer surfaces low-confidence responses to a review queue or to a human-in-the-loop step before reaching the user.

Our engagement controls are SOC 2-aligned and HIPAA-aligned. We sign BAAs before any PHI is shared, we pin LLM inference to a US region when the engagement requires it, and we will run the entire RAG build inside your AWS, Azure, or GCP account if your security team requires customer-managed encryption and a zero-egress data path. The vector store, the BM25 index, the reranker, and the LLM can all run inside your VPC. Audit logs on retrieval and generation events are exportable for SOC 2 evidence and HIPAA forensic review. Self-hosted Llama 3 on vLLM is supported for engagements that cannot route to third-party APIs.

Your call. We default to AWS US-East-1 or US-West-2 for US clients, but we will run inside your AWS, Azure, or GCP account in any US region you specify. For clients with strict data-residency requirements (federal, healthcare, defense-adjacent), we deploy single-region with no cross-region replication and no inference egress to non-US LLM endpoints — Claude and GPT-4o have US-region endpoints we route to explicitly, or we self-host Llama 3 on vLLM inside your VPC for zero third-party inference. The vector store and BM25 index stay in your account.

Senior engineering rates at Aiinfox are roughly 30 to 50 percent lower than equivalent Bay Area, NYC, or Boston RAG consultancies — real, but not the headline. The headline is the delivery model: senior engineers only, fixed-price six-week RAG scopes, overrun cost on us if we miss for reasons on our side. Most Bay Area shops bill timesheets, run discovery-then-discovery-then-build phases, and either burn a junior pool behind a senior nameplate or churn senior staff onto bigger accounts mid-engagement. We bill shipped systems and keep the same engineers on your build through launch.

Yes — RAG rescue audits are routine. Step one is reading the chunking code, the retrieval logic, the eval results (if any), and the answer-layer prompts. Step two is shipping the smallest valuable change to prove we understand the system — usually adding the eval harness or fixing the chunking strategy that the previous vendor skipped. Step three is the longer-term rebuild plan if one is needed. Most RAG rescues we see did not need a rewrite — they needed hybrid retrieval, citation enforcement, and an eval bar. We will be honest on the first call about which category your project lands in.

Yes. MSA-plus-SOW for ongoing relationships, single-document fixed-price agreements for one-off RAG pilots. Standard terms cover IP assignment (your retrieval logic, your corpus, your IP), limitation of liability, indemnification, data handling, and a 30-day production warranty. Net-30 invoicing for established engagements; pilots are typically 50 percent upfront, 50 percent on acceptance. We are a registered Indian entity (Aiinfox Pvt. Ltd.) invoicing US clients in USD via wire transfer — no W-9 or 1099 entanglement because we are a foreign corporation.