Grounded RAG agents
Retrieval-augmented agents with citation and provenance. Pgvector, Pinecone, weaviate, your existing store.
AI consulting in the USA — production agents at enterprise scale.
Nationwide AI consulting from US-headquartered senior teams. Production AI agents grounded in your data, governed by your rules, observable end-to-end. 20 years of enterprise delivery behind every implementation.
20 yrs
Enterprise delivery from Virginia
100%
Senior engineers on every client-facing role
ISO 12207 + 27001
Certified delivery + infosec
US enterprise AI is mostly governance, not models.
AI feature quality has converged across model providers. The differentiator at enterprise scale isn't whether your agent uses GPT-5 vs Claude vs Gemini — it's whether your agent is governed, audited, observable, and rollback-able. Most US enterprises with AI pilots stuck in pilot are stuck because governance and operations are unsolved, not because the model isn't smart enough.
NETLINKS' US AI work starts from operations: every production AI system we build has full audit logging (every prompt, response, tool call, model version), guardrails (explicit allow-lists for actions, content moderation, sensitive-data filtering), human-in-the-loop gates on regulated decisions, observability (latency, cost, accuracy, drift tracked in real-time), and rollback paths (model-version pinning, kill switches, fallback to deterministic logic).
Multi-year managed-services follow most builds. Pricing: discovery + pilot $50-150K, production deployment $150K-$1M+, managed services 15-25% of build cost annually.
— AI scope
What we build.
Agentic workflows
Multi-step agents with tool use, human-in-the-loop gates, state machines.
AI governance
Audit logging, guardrails, content moderation, model evaluation, drift monitoring.
Odoo-embedded AI
AI inside Odoo — invoice classification, ticket triage, procurement query handling.
Model strategy
Multi-provider routing via Vercel AI Gateway. Cost / latency / accuracy trade-offs.
AI enablement
Training, prompt engineering, evaluation methodology, responsible AI policy.
— Questions
USA AI consulting — questions we hear.
Do you build with GPT, Claude, Gemini, or open-source?
All of them — we route per use case. Most production systems use 2-3 model providers with explicit routing rules via Vercel AI Gateway or equivalent. We're model-agnostic; the architecture lets you swap providers without rewriting the agent.
Can you build for HIPAA / SOC 2 / FedRAMP-adjacent compliance?
Yes for HIPAA and SOC 2 (we hold ISO 27001 which aligns with most controls). For FedRAMP-authorized SaaS, we don't currently hold the authorization for our own products but we work on FedRAMP-adjacent integrations (e.g., AI agents that consume FedRAMP-authorized data sources).
How do you handle AI cost optimization?
Token-level cost tracking on every prompt, automatic routing of low-complexity queries to cheaper models, prompt-caching where supported (Anthropic / OpenAI both offer this), and explicit cost budgets per use case with alerts on overage.
What about RAG over our existing enterprise content?
Common engagement pattern. We ingest your Confluence / SharePoint / Google Drive / S3 / file shares, index with embedding model + vector store of choice, add metadata filters for access control, and serve via your agent platform of choice (custom, Slack, Microsoft Teams, web).
Are you a small business?
Yes — NETLINKS Inc is a small business by SBA standards. Specific certifications on request.
How do I get started?
30-min discovery → scoped proposal → engagement. Most engagements start with a paid structured discovery that ends in a written design + firm fixed-fee proposal.
Scope a US AI engagement with senior engineers.
30-min discovery → paid pilot → production deployment with full governance.
Start the scoping