Generative AI on your own data — without hallucinations.
Retrieval pipelines, fine-tuned domain models, multimodal apps and eval suites. Built so your team can trust the output enough to ship it.
- Retrieval pipelines
- Fine-tuned domain models
- Multimodal (text · image · voice)
- Eval + guardrails
How it works
Our flow — from kickoff to production.
- 1Step 1
Data inventory
What docs / databases / APIs / feeds matter? What's PII vs public? What changes daily vs quarterly? We map it before writing code.
- 2Step 2
Retrieval architecture
Hybrid (BM25 + vector) retrieval, chunking strategy, reranking, citations. Tuned for your domain not a generic benchmark.
- 3Step 3
Eval suite
Real-world question set with golden answers. Faithfulness, context precision, latency. So you know when changes ship a regression.
- 4Step 4
Guardrails
Prompt-injection defense, PII scrubbing, refusal patterns, output schemas. Especially critical for customer-facing deployments.
- 5Step 5
Production + iterate
Cost-effective inference (caching, fallback models), monitoring, weekly eval reports. Fine-tune when the data justifies it.
What you get
Components & deliverables
- From $7,500
RAG Pipeline
End-to-end retrieval pipeline on your data. Source-cited answers, freshness controls, and multi-tenant isolation.
- From $5,500
Domain Fine-tune
When prompting isn't enough — fine-tune Llama / Mistral / GPT on your historical conversations or annotations.
- From $2,500
Eval Harness
Versioned eval set, regression dashboards, A/B prompt testing. Lets you ship faster, not slower.
- From $9,000
Multimodal Apps
Text + image + voice combined. Document understanding, vision QA, voice-driven workflows.
- From $1,800
Prompt-Injection Hardening
Red-team your LLM endpoints. Defense layers, input/output filters, structured outputs.
- From $1,500
AI Cost Optimization
Caching, model routing, batch processing. Typical savings 40–70% on inference bills.
Pricing
RAG build from $7,500. Eval harness from $2,500. Production retainer (model ops + iterations) from $1,400/mo.
Pricing ladder
After this, where most clients go next.
Sprint validates · Build productionizes · Retainer scales. The Sprint fee credits toward Build.
Step 1 · Validate
30-day Sprint
Prove the use case before you commit. Working prototype on real data, eval scores, and an honest signal in 30 days. Fixed scope, fixed fee.
$4,500 fixed
Learn more- Most teams land here
Step 2 · Build
Prototype → Production
Turn the validated prototype into a real product. Auth, DB, payments, tests, monitoring, deployed. Sprint fee credits toward this engagement.
from $6,000
Learn more Step 3 · Scale
Managed Retainer
Ongoing operation, eval cycles, model iteration, and cost guards. We keep the system improving so your team can focus on growth.
from $750/mo
Learn more
FAQ
Questions we get a lot.
RAG for facts that change. Fine-tuning for style, format, or domain reasoning. Most production systems use both — and we'll tell you which mix is right after a 1-week discovery.
Contact
Talk to us about Generative AI & RAG.
Tell us where you are now and where you want to be. We reply within one business day.
Or skip the form — book a Calendly slot directlyadmin@neuroxai.com · +91 70149 99768
Remote-first team across India · US · EU · HQ in Udaipur, India