Voltify helps engineering and product teams integrate custom foundation models, production RAG pipelines, and automated agent workflows into their existing AWS infrastructure — with zero model-training risk and no vendor lock-in.
AWS Bedrock is the right foundation for regulated, multi-model enterprise AI: VPC-isolated inference, native guardrails, KMS-encrypted storage, and a catalog of providers (Anthropic, Meta, Amazon) under one control plane. The gap is execution. Most teams underestimate the work of routing models safely, grounding answers in real data, and hardening the pipeline for production.
Customer data never leaves your AWS trust boundary and is never used to train base foundation models (Claude, Llama, Titan, etc.).
Encryption at rest with your AWS KMS keys; inference traffic over TLS 1.3. You control the keys, not us.
Models run inside your existing AWS VPC with fine-grained IAM role access. No public exposure required.
Deployment patterns designed to align with SOC 2 Type II controls — access, logging, change management, and audit trails.
Architecture supports HIPAA workloads with BAAs executed under the enterprise engagement where applicable.
Deployment follows information-security controls aligned with ISO 27001 — inventory, access control, monitoring, and incident response.
Enterprise buyers hesitate when purchasing open-ended "agency hours." We productize the engagement into three phases, each ending with a concrete deliverable you can review and decide on — not just calendar time.
Architecture & Feasibility Audit
You end Phase 1 with a documented architecture, a realistic cost model, and a clear yes/no on feasibility — before any build work starts.
RAG & Pipeline Build
You end Phase 2 with a working pipeline in a staging environment, grounded on your data, with guardrails in place — demonstrable, not promised.
Production Deployment & Guardrails
You end Phase 3 with the pipeline live in your environment, cost and latency visible, and runbooks your team can own — not a handoff you have to relearn.
The durable case for hiring Voltify isn't "you can't build this yourself." It's that we remove specific, expensive problems so your team can focus on the product — not on IAM/VPC design, model routing, guardrails, cost monitoring, and production hardening.
| Capability | Standard API wrappers | In-house build | Voltify on AWS Bedrock |
|---|---|---|---|
| Data privacy | Public cloud risk | Variable | 100% private VPC isolation |
| Model flexibility | Locked to single vendor | High maintenance | Multi-model dynamic routing |
| Guardrails & safety | Basic prompt filters | Custom engineering required | Native AWS Bedrock guardrails |
| Time to production | Weeks | 3–6 months | Under 30 days |
| Cost & latency observability | Surprise bills | Build it yourself | CloudWatch dashboards from day 1 |
| IAM / VPC / security design | Often skipped | Heavy lift | Designed into the engagement |
| Staging → production handoff | Ad hoc | Often incomplete | Runbooks + observability included |
A 4-week production deployment of a RAG-backed AI assistant or agent workflow inside your AWS account, with a security/architecture blueprint, a working staging pipeline, and a production launch with observability.
This is a short diagnostic so we can tailor the architecture blueprint and audit to your situation. It takes about two minutes.
Tell us about your AWS footprint and use case. We'll respond within one business day with a tailored blueprint and audit options.
Engineering and product teams already on (or moving to) AWS who want to deploy custom foundation models, production RAG, or agent workflows inside their own VPC — with a clear 30-day path to production and a partner who handles the security, routing, and observability work.
Teams looking for a ready-made SaaS they can sign up for in a click (use the Bedrock app instead), or teams unwilling to operate inside their own AWS account. If you want a vendor-managed black box with no VPC involvement, this engagement isn't a fit.
