AI for dental and healthcare practices
- Answer and book new-patient calls
- Appointment reminders and rescheduling
- Front-desk handoff for clinical questions
AI that makes it to production.
AI Consulting & Implementation
We find the AI use cases worth building, ship them into the systems your team already uses, and keep them running after launch. Strategy, engineering, and ownership from one accountable team, not a slide deck and a goodbye.
- AI agents
- Workflow automation
- AI inside your apps
- Governed from day one
- Answer every call
- Book the appointment
- Read the invoice
- Route the lead
- Draft the reply
- Check the freight rate
- Summarize the meeting
- Find the policy
- Flag the exception
- Update the CRM
- Qualify the enquiry
- Reconcile the readings
What is AI consulting and implementation?
AI consulting finds where AI will create measurable value in your business. AI implementation builds those use cases into your real systems, tests them against real cases, and keeps them running. Charviam does both with one team: a two-week readiness sprint, then a production build in four to eight weeks.
- Two-week AI Readiness Sprint
- First step
- 4 to 8 weeks after the sprint
- First use case live
- Forward-deployed engineers in your tools
- Who does the work
- Monitoring, guardrails, and a named owner
- After launch
Why do most AI pilots never reach production?
The problemThe model is rarely the reason. Pilots stall on the unglamorous parts: data, integration, and ownership. That is where we spend our time.
95%
The demo never met real data
It worked on ten clean examples. Your actual records are messy, scattered, and full of exceptions nobody wrote down.
Nobody connected it to the work
A chatbot in a browser tab is not a workflow. Value shows up when AI reads from and writes to the systems your team already uses.
Nobody owns it after launch
Models change, costs creep, answers drift. Without monitoring and an owner, a good pilot quietly becomes a liability.
How ready is your business for AI?
AI Readiness ScoreSix questions, about a minute. You see your score and a suggested first use case right away, no email needed.
- Takes about 60 seconds
- Scores data, ownership, volume, and timing
- Recommends where to start and what to build first
Question 1 of 6
Where does your team lose the most time?
How does AI implementation work?
How we engageIn four steps. Each one is useful on its own and sets up the next, so you start with the smallest step that proves value. Most clients begin with the readiness sprint.
012 weeks
AI Readiness Sprint
We map how work actually flows, find where AI pays for itself, and check your data before anyone writes a prompt.
- Workflow and data review
- Top three use cases ranked by return
- Risk and governance check
- A 90-day plan you can act on
024 to 8 weeks
Pilot to Production
One use case, built into your real systems and proven against real cases before your team relies on it.
- Working integration, not a demo
- Evaluation against your real cases
- Guardrails and human handoff
- Monitoring and team training
03Monthly
Forward-Deployed AI Engineer
An engineer embedded with your team, shipping AI features and automations alongside your people.
- Works in your tools and standups
- Ships into your codebase and stack
- Builds your team's AI skills
- Stays accountable for what ships
04Ongoing
AI Run & Govern
We keep what we built accurate, affordable, and compliant as models, prices, and rules change.
- Quality and drift monitoring
- Model upgrades and cost control
- AI usage policy and access review
- Monthly report you can share
Not sure where AI fits yet?
Tell us what takes your team the most time. We'll tell you honestly whether AI is the right fix.
AI consulting vs. AI implementation: what's the difference?
Consulting or implementation?Consulting tells you what to build. Implementation builds it. Most AI projects stall in the gap between the two, so we do both with one team.
| Compare | AI consulting | AI implementation | Charviam (both) |
|---|---|---|---|
| What you get | A roadmap and recommendations | A working system in production | The roadmap, then the working system |
| Typical timeline | Weeks | Weeks to months | 2-week sprint, first use case live in 4 to 8 weeks |
| Who builds it | Usually your team or another vendor | The implementation partner | The same engineers who scoped it |
| After launch | Out of scope | Often a handoff | Monitoring, cost control, and a named owner |
What can AI automate in your business?
What we buildMore than chat. We start from the work, not the technology, and these are the places we see AI pay for itself most often.
AI phone and front-desk agents
Answer every call, take the order or book the appointment, and hand off to a person when it matters.
Read the pizzeria storyWorkflow automation
Move data between the tools you already pay for, with AI handling the reading, sorting, and drafting in between.
See the ready-made AI automationsKnowledge and document assistants
Answers drawn from your own policies, manuals, and records, with the source shown so people can check it.
Talk to us about your documentsAI inside your product
Search, summaries, recommendations, and agents built into the app your customers already use.
See how we build productsAI search visibility
Get your business cited when buyers ask ChatGPT, Gemini, and Google's AI answers who to call.
See SEO and AEOOperations and finance checks
Invoices, rates, and readings checked automatically, so people review exceptions instead of every line.
Read the freight invoice storyAI solutions by industry
By industryThe same building blocks, shaped around how each kind of business actually runs.
AI for restaurants and hospitality
- Take phone orders during the rush
- Answer hours, menu, and booking questions
- Catering and large-order intake
AI for home and auto services
- After-hours call answering and booking
- Job intake with the right details
- Quote and follow-up reminders
AI for staffing and recruiting
- Candidate screening and scheduling
- Onboarding paperwork automation
- CRM updates without retyping
AI for manufacturing and operations
- Exception alerts from machine and quality data
- Schedule changes when a line goes down
- Shift reports written for you
AI for distribution and logistics
- Carrier invoices checked against agreed rates
- Shipment status answers for customers
- Document and order data extraction
We send an engineer, not a slide deck
How we workFive steps, and every one ends with something you can hold, check, and keep.
- 01
Discover
We sit with the people doing the work and trace where time and money actually go.
You get: Workflow map
- 02
Prioritize
Each idea is scored on value, data readiness, and risk, so the first build is the one most likely to pay off.
You get: Ranked use-case list
- 03
Build
We build inside your systems with your data, not in a separate sandbox nobody will ever connect.
You get: Working integration
- 04
Prove
Before launch, the system is tested against real cases and the results are written down.
You get: Evaluation report
- 05
Run
Monitoring, cost tracking, and a named owner keep it working after go-live.
You get: Runbook and monthly report
We run AI in production every day
Proof, not a pitchSanma, our AI agent for phone calls, chat, and texts, answers real calls for real businesses: taking orders, booking appointments, and handing off to staff when a call needs a person. Here is what its owners say.
How do you keep AI safe and compliant?
Safe by defaultBy putting the rules in place while we build, so you are never retrofitting them under pressure after the first incident.
Your data stays yours
We use providers and settings that do not train on your data, and we only connect the systems a use case needs.
A person where it matters
Refunds, medical questions, and anything unusual go to a human. We design the handoff before we design the prompt.
Access and audit built in
Role-based access, logged actions, and an off switch, set up by the team behind our Access & Security service.
Ready for the rules
Clear AI disclosure for customers and a written usage policy, so new regulations land as paperwork, not a rebuild.
AI consulting and implementation FAQ
FAQAn AI consultant works out where AI will save time or money in your business, checks whether your data and systems can support it, and ranks the options by return and risk. At Charviam the same engineers then build the top use case into your systems, so the advice and the delivery never come apart.
Three things matter most: a repetitive task with real volume, data you can reach, and a person who will own the system after launch. Take the 60-second AI Readiness Score on this page for a quick read, or book a two-week readiness sprint for a full assessment.
An AI agent is software that can understand a request, decide what to do, and take action in your systems, such as answering a call and booking the appointment, rather than only producing text. Good agents work within clear limits and hand off to a person when a situation needs judgment.
It depends on the use case and how much of your stack it touches, so we scope it with you rather than quote a number off a page. Most clients start with a two-week AI Readiness Sprint, which gives you a ranked list of use cases and a realistic budget for each before you commit to a build.
A focused first use case usually reaches production in four to eight weeks after the readiness sprint. Simple automations can be faster. We would rather ship one thing that works than five pilots that never leave the demo.
We build on providers and settings that do not use your data for training, connect only the systems a use case needs, and keep access logged and limited. If you have specific requirements, such as HIPAA or a data processing agreement, we work within them from the first week.
Whatever fits the job and your budget. We work across the major model providers and automation platforms such as n8n, Zapier, and Make, and we design so you can switch models later without rebuilding everything.
It will, sometimes, which is why we plan for it. Every system is tested against your real cases before launch, risky actions require a person to approve them, and monitoring flags drops in quality so they get fixed instead of discovered by a customer.
That is not how we design it. The goal is to take repetitive work off your team, like answering the same call for the hundredth time or retyping invoices, so people spend their time on the work that needs judgment.
Yes. We start by finding out why it stalled, which is usually data, integration, or ownership rather than the model itself. Sometimes the right move is to fix the pilot; sometimes it is to pick a better first use case.
Both. Sanma, our AI agent for phone calls, chat, and texts, is built and run by Charviam and is live with businesses like pizzerias, dental practices, and HVAC companies. That experience of running AI in production every day is what we bring to your project.
Bring one process. We'll show you where AI fits.
Start with a two-week AI Readiness Sprint and leave with a ranked plan, whether or not you build with us.
Book an AI Readiness Sprint