People and departments
Manage users with their departments. Turn AI access on or off, and see which person and team a call came from.
Order and accountability in access decisions.
DataSynca AI Gateway
The power of AI.
Under your
control.
Give people room to do more with AI. Decide who can use which models, what data may be shared, and how the budget is spent — from one place.
AI GatewayCompany rules on
Employee chatDeveloper toolsApplications
DataSynca AI Gateway
Access rightsData rulesBudget checkUsage tracking
OpenAIClaudePrivate model
The request was judged against the rules you defined.
A diagram of how the path works.
Simple for employees
A clear way to reach the AI you have approved.
Manageable for IT
Scattered use brought under one set of rules.
Visible for leadership
Usage, spend, and rule outcomes in one view.
Company AI needs a company order
Let innovation move.
Do not leave control behind.
One team drafts a proposal. Another writes code. Finance summarizes a long report. As AI becomes part of the work, access, data sharing, and cost need one shared frame.
DataSynca AI Gateway is the access point your company runs for that use. People stay on the work. Admins follow the rules, the permissions, and the usage in the same place.
A solid base for wider AI use: easy access, explicit rules, and measurable usage.
What it supports
One access point.
Controls that work together.
Bring the main decisions of AI use together: the employee experience, data sharing, model choice, and budget.
Approved models
Connect OpenAI, Claude, and a compatible model on your own server. Choose which models people may use, and change that as needs change.
Model choice stays with your company.
A key for each person
Issue access keys for compatible apps and developer tools. Manage and revoke access without handing out the provider’s own key.
Central control, individual access.
Mask or stop sensitive content
Write rules for the fields, phrases, and data classes you choose. Send what is allowed. Mask a sensitive value, or stop the request, when a rule says so.
Your limits on what data is shared.
An extra review on your own model
Use a private model connection as a content check. A request headed for an external model passes the review step you defined.
A stronger content review when you need one.
Usage and spend
Set a person’s budget, watch consumption, and raise the limit when you decide to. See cost calculated from the model prices you entered.
A more predictable way to run AI spend.
Overview and activity
Read usage on the overview. Find a call with activity filters, and review access, the rules that ran, and the outcome.
Answer questions from the record.
Try a rule, then publish it
Evaluate rules with sample input, publish them, and keep the change history. Return to an earlier version when you need to.
Change rules with a record behind you.
A setup that fits your company
Run DataSynca on your own infrastructure or in an environment reserved for you. You choose the AI providers and what those providers may see.
AI control that matches how you host.
Two ways in, one way to manage
Business teams can chat.
Developers can stay in their tools.
For employees
Company AI chat
People sign in to the chat, pick a model they are allowed to use, and start the work. Requests are judged against company rules and budget.
Example
Can you turn these meeting notes into an action list?
Draft actions: sales updates the proposal; operations confirms the delivery date.
Text-first work, with supported TXT, Markdown, and CSV files attached to the chat.
For developers and apps
Access from the tools you already use
Use AI from a compatible IDE extension or app with the gateway address and a personal API key. Access, content, and budget stay under one control, whichever tool sends the call.
Example access path
Personal keyVerified
Company rulesApplied
Approved modelRequest sent
Used with clients that can set a gateway address and a personal API key, such as VS Code.
How it works
Between the request and the model
are your company’s decisions.
Someone sends a request.
They reach AI from chat, a compatible developer tool, or an application.
Access and rules are checked.
User rights, model permission, content rules, and budget are evaluated.
Allowed content goes to the model.
The request is sent, sensitive values are masked, or the call is stopped — according to the rule.
Usage becomes visible.
Admins follow outcomes, consumption, and what the rules did.
Familiar work, with a company frame
The value shows up
in the daily work.
See how AI Gateway can sit beside the way different teams already work.
Speed up customer writing.
Put a rule on sensitive fields.
Sales wants a customer email rewritten more clearly. The company marks the customer number as a sensitive field. A mask rule helps keep that matching value from being sent to the model in the clear.
The draft still gets written, inside the data-sharing frame the company set.
A field in the requestCustomer no: 458210
“Rewrite the delivery note more clearly.”
“Rewrite the delivery note more clearly.”
After the mask ruleCustomer no: ***
“Rewrite the delivery note more clearly.”
“Rewrite the delivery note more clearly.”
Spread coding help.
Tie access to a person.
The engineering team uses an approved model from a compatible VS Code extension. Each developer connects with their own gateway key. The company does not have to hand out the provider key.
Access is easier to grant, revoke, and follow per person.
What they need“Suggest tests for this function.”
What the company controlsPersonal access key
Approved model · User budget · Activity record
Approved model · User budget · Activity record
Grow AI use.
Keep the budget visible.
As more departments start using AI, leadership wants to see where use is heaviest. Personal budgets and the cost view answer that on one admin screen.
Extra budget decisions rest on recorded use, not on a guess.
The question“Which team is using how much?
Whose budget should we raise?”
Whose budget should we raise?”
What you can seeUsage and consumption
Personal budgets · Model prices · Request outcomes
Personal budgets · Model prices · Request outcomes
These are illustrative examples. The control that runs depends on the rule you defined, the model in use, and the content types that are supported.
The admin view
Visible use.
Clearer decisions.
Run AI governance from one view, not from scattered questions.
See who used it.Look by person and by department.
See why it stopped.Follow the rule decision and the outcome.
Move the budget with the need.Watch consumption and raise a limit when you choose to.
AI Gateway / OverviewIllustrative view
What you trackUsageBy person and model
What you trackCostFrom the prices you set
Activity · Example outcomes
Sales · DraftMasked
Engineering · Code helpAllowed
Operations · Data shareBlocked
A design that explains the product. It is not a screenshot and it is not customer data.
Before you buy
Expectations stay clear.
Control stays with you.
Do people have to abandon the AI tools they already use?
They can use DataSynca’s chat, or keep a tool that can be pointed at the gateway address and an API key. Whether a specific client and model combination fits is checked as part of the setup.
Can we use the AI providers we already have?
You can connect supported providers and a compatible model on your own server. Your company decides which models are available and which data they may see.
Is every use of AI monitored automatically?
The controls apply to use that passes through DataSynca AI Gateway. A person who opens another AI site directly is outside that path. A company-wide approach still depends on approved tools and the rest of your security measures.
How are sensitive data and cost handled?
Content is judged against the rules you defined. A match can be masked or the request can be stopped. An extra check on a private model can be added. Cost follows the model prices and the usage the provider reports; the check model can consume budget too. No automatic content check can promise to catch every sensitive value.
Can we run it in our own environment?
DataSynca can be installed on your own infrastructure or in an environment reserved for you. When you choose an external AI provider, the content you allow is sent to that provider. The private-model choice and the data-sharing rules are planned together for that reason.
Next step
Give your people the power of AI.
Do not leave the management to chance.
Let’s look at the first team, the models you want, and the data rules together. We’ll judge AI Gateway against a real way your company works.
Plan a conversation for your company Explore DataSynca →