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Salvus AI
AI & Implementation

An AI assistant built on your data, wired into your workflow.

We build LLM assistants, retrieval-augmented generation systems, and voice agents trained on the content and context your team actually uses. No generic chatbot. A system that knows your business.

Scope this serviceGet a written quote

Engagement details

Quote
In writing
Duration
4 to 12 weeks
Models
Leading models across 5 providers
Integrations
CRM, calendar, ticketing, internal data
Voice AI
Included
Ownership
Your repo, your data
How this engagement runs

Three steps from first call to system you own.

  1. 01

    Scoping

    We pick where this moves a number.

    Working session, written read-out, 1 to 3 places this service actually moves the needle for your business.

  2. 02

    Build

    We ship on your infrastructure.

    Code lands on your server, wired into the tools your team already uses. You see progress every week.

  3. 03

    Tune

    90 days of weekly edits.

    Weekly tuning calls, accuracy reporting, and a single weekly number that says working or broken.

Inside the engagement

What you actually receive.

  • 01LLM

    LLM assistants

    Conversational AI built on leading models across 5 providers. Tuned to your tone, your data, your policies. Not a wrapper around a generic product.

  • 02RAG

    Retrieval-augmented generation

    Connect the model to your documents, your CRM, your knowledge base. Answers grounded in your actual content, not hallucinated from training data.

  • 03Voice

    Voice agents

    Inbound and outbound voice AI via Twilio, ElevenLabs, and Vapi. Handles after-hours intake, appointment reminders, and follow-up calls without a human on the line.

  • 04Integration

    CRM and tool wiring

    The AI connects to your existing stack. Reads from and writes to your CRM, calendar, ticketing system, and internal data sources.

  • 05Audit

    Auditable logs

    Every model call logged with timestamps, inputs, and outputs. Compliance teams get what they need. You see exactly what the AI is doing.

  • 06Ownership

    Code you own

    All source lives in your GitHub org from day one. We commit, you review, you keep it forever.

Method

Predictable phases. Honest checkpoints.

  1. 01Week 1
    Phase 01

    Scope and data audit

    We map your data sources, workflows, and use cases. Written scope by end of week one.

  2. 02Weeks 2 to 4
    Phase 02

    Build and integrate

    Model configured, retrieval layer built, integrations wired. You see it running on real data.

  3. 03Weeks 5 to 8
    Phase 03

    Test and tune

    Your team runs it. We tune on real usage. Edge cases get handled before launch.

  4. 04Week 8+
    Phase 04

    Launch and handoff

    Full runbook. Named owners. On-call support for the first 30 days. Production go-live.

A voice agent handles after-hours calls and an AI assistant supports the front desk every day. Both were built and run inside the practice's own operation.
Client successClient win/Name withheld

Next step

Ready to scope custom ai development?

Thirty minutes on the phone, and you will leave with a clear answer on whether this fits. Not a soft proposal, a yes or no.

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