Ravan.ai

THE RAVAN APPROACH

From prototype.
To everyday use.

Your Ravan engineers help you choose a business problem, build and test the AI, connect it to your software, and train the people who will use it.

BUSINESS CONTEXT ENGINEERING EVERYDAY USEInside the engagement

CLOSE TO THE WORK

You know your business.
We build the AI.
We work as one team.

We learn how your business works before deciding what to build. Then we connect the AI to your data and software, test it on real tasks, and help your team use it confidently.

HOW THE WORK MOVES

From your first prototype.
To the result you want.

See what you get at each stage, and what we agree before moving forward.

01 / 04Understand the business problem.

We agree the scope, timing, and cost before work starts.

UNDERSTAND THE WORK

Choose the problem
to solve.

We talk to the people doing the work, review your systems and data, and measure how the process performs today. Together, we choose a clear goal for the first project.

We define together
The problem, who owns it, today’s performance, and the target result.
Ready for review
A written plan: what we will build, what we need, and how we will measure success.
THE DECISION WE SHARE

Is this the right first problem?

A problem worth solving, with the data and people needed to begin.

BUILD & EVALUATE

Build and test
a prototype.

Test a working prototype with your data and users. Check whether it gives useful answers, handles unusual cases, and asks a person for help when needed.

We define together
What a good result looks like, test examples, and when a person must review the AI.
Ready for review
A working prototype, test results, and a list of issues to fix.
THE DECISION WE SHARE

Does it perform well enough for the next step?

The evidence to decide what is ready—and what needs more work.

DEPLOY WITH INTENT

Connect it.
Launch it safely.

Connect the AI to your software, set permissions and approval steps, and plan how to handle failures. Roll it out with your IT and business teams.

We define together
Where the AI runs, which systems it connects to, and who approves the launch.
Ready for review
AI connected to your software, launch checks, and a support plan.
THE DECISION WE SHARE

Can your team run it with confidence?

A planned launch, with access rules, human approvals, and named support contacts.

ADOPT & IMPROVE

Train your team.
Keep improving.

Train your people on real tasks. Measure how the AI performs against your starting point, listen to user feedback, and improve the system after launch.

We define together
Staff training, ways to report issues, review dates, and support responsibilities.
Ready for review
A report on usage and results, plus an agreed list of improvements.
THE DECISION WE SHARE

What should get better next?

A continuing team that knows the system, the people, and the outcome.

THE WORK KEEPS TEACHING US

Every release.
A better starting point.

01Learn from use

02Evaluate the change

03Improve the workflow

Your team’s feedback and test results guide each improvement.

YOUR IN-HOUSE AI TEAM

Who does what.
Agreed from the start.

Ravan works alongside your business, engineering, IT, and security teams. The engagement makes each person’s role explicit.

The workYour team bringsRavan brings
Business direction

Priorities, process knowledge, and a business owner.

A review of the task, recommended technology, and a delivery plan.

The system

Access, standards, and decisions on your environment.

AI software, connections to your systems, testing, and launch.

Everyday operation

Staff who use the system, make decisions, and share feedback.

User training, system monitoring, and ongoing improvements.

Specific responsibilities, access, support, and ownership terms are agreed for your engagement.

BEFORE PEOPLE DEPEND ON IT

Ready for
real work.

These questions shape the system from the beginning.

Where will the AI run?

We review your data policies, existing servers, cloud setup, and budget. Then we agree where the AI will run and explain any external services it needs.

What can the system see and do?

We agree which documents and systems the AI can access, what it can change, and which actions need a person’s approval.

What happens when it gets something wrong?

We test difficult cases and errors before launch. We decide when the AI should stop, ask a person for help, or use a backup process, and record issues so they can be investigated.

How will people learn to use it?

Your people try the system during development. We train them on real tasks, explain how to check results, and use their feedback to improve it.

How are timing and pricing set?

Your proposal sets out what we will build, the systems to connect, the team, delivery dates, fees, and ongoing support. We agree these details before work begins.

YOUR NEXT CHAPTER

Let’s put AI
to work.

Tell us what needs to improve.
We’ll help you choose the first AI project.

LET’S PUT AI TO WORK

Start a conversation.

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