Start with existing assets
Tables, relationships and services form the project foundation. ADA’s backoffice can work alongside ERP, CRM and internal applications.
ADA Enterprise
AI on your data.
Inside your processes.
We connect ADA to databases and services already in production. Your data model becomes a backoffice; agents query information and turn team requests into operations. In your tools, with your access rules.
Existing databasesGenerated backofficePrivate AI options
FROM DATABASE TO BACKOFFICE
Your existing databaseTables · Relationships · Views
ConnectedData model and access rules
ADABACKOFFICECustomersOrdersProducts
Your operational foundation is generated from the model.
Records and formsSearch and filtersAPIs and AI tools
From questions to analysis
Complex queries.
Straightforward questions.
Which customers are ordering less? Where are margins falling? Which cases are blocking a process? An integrated chatbot translates team requests into queries on connected data and returns results to review and explore.
Metrics, relationships and data scope are defined with the people who know them. For analysis that reflects your business and results you can verify.
ADA DATA WORKSPACEDemo data›Compare revenue and margin by channel for the last quarter.
Quarterly revenue€1.28 M
Overall margin32.4%
| Channel | Revenue | Margin |
|---|---|---|
| Marketplace | €610,000 | 32.8% |
| Direct | €420,000 | 38.1% |
| Partners | €250,000 | 22.0% |
The direct channel has the highest percentage margin. The marketplace generates the largest share of revenue.
Explore the example query
SELECT channel, SUM(revenue) AS revenue,
SUM(revenue - cost) / NULLIF(SUM(revenue), 0) AS margin
FROM analytics.sales
WHERE sold_at >= :quarter_start AND sold_at < :quarter_end
GROUP BY channel
ORDER BY revenue DESC;›Find orders over €5,000 that have been delivered but are still awaiting payment.
Orders to review3
Total order value€24,600
| Order | Country | Amount |
|---|---|---|
| ORD-2196 | Germany | €9,800 |
| ORD-2084 | Italy | €8,400 |
| ORD-2301 | France | €6,400 |
There are 3 orders to review in this example. Open their details and assign the check to the appropriate team.
Explore the example query
SELECT order_id, country, amount
FROM analytics.orders
WHERE amount > 5000
AND delivery_status = 'completed'
AND payment_status = 'pending'
ORDER BY amount DESC;›Which onboardings have been stuck for over 48 hours? Show me the missing step.
Cases to resume3
Review threshold48 h
| Customer | Pending step | Waiting |
|---|---|---|
| Company Alpha | Documents | 78 h |
| Company Beta | Service | 63 h |
| Company Gamma | Documents | 51 h |
There are 3 cases to pick up. Two are awaiting document checks and one is awaiting service configuration.
Explore the example query
SELECT account, pending_step, hours_waiting
FROM analytics.onboarding
WHERE hours_waiting > 48
AND status = 'pending'
ORDER BY hours_waiting DESC;An operational foundation alongside your systems
Connect the database.
Your backoffice takes shape.
ADA connects to your existing database, including production systems. Once the data model and access are configured, it generates records, forms and AI tools from entities and relationships. Teams can start searching and managing information without building every screen from scratch.
Choose what to make available
We define entities, views, actions and permissions. From reading to updating records, with the controls your process requires.
Extend where needed
Add specialised modules, agents and interfaces for each department. The same foundation exposes APIs and tools for AI.
The LLM can be the channel itself
Claude. ChatGPT.
Your internal assistant.
ADA exposes data and actions through MCP connectors and APIs. Connect Claude or ChatGPT to business systems, embed a chatbot in your backoffice or bring an agent into your team’s tools. AI becomes a way to get work done, within a defined scope.
We configure identity, permissions and exposed tools for each integration. The model accesses the actions you choose to enable.
ClaudeChatGPTYour AI
An example request
“Which orders have a margin below 15%? Group them by channel and show me the anomalies.”
Data and tools connected through ADA
OrdersMarginsChannels
A connection to your data, with actions and access configured for your project.
From information to operations
Keep work moving.
Including the repetitive parts.
Review a case, collect information across systems, prepare an update or flag an anomaly. ADA agents can follow these steps and call enabled actions within a process designed with your team.
Each workflow defines what runs automatically, what needs confirmation and how errors are handled. Relevant actions are logged so you can reconstruct what happened.
Example: unblocking an order
AI identifies the case
An order is on hold because a document is missing.
It prepares the next step
It collects the details and prepares a request for the owner.
Your rules determine what happens
Team approval or an automatic action, according to the defined process.
Architecture for your workload
Large volumes.
An architecture to match.
The chatbot is the entry point. Behind it, you need a sound data model, efficient queries and an architecture designed for real workloads. We plan the path with you, from operational databases to analytics systems.
Large-scale analytics
PostgreSQL, DuckDB and ClickHouse, depending on the context. Views, aggregations and optimised queries make complex analysis accessible without pouring entire datasets into the AI model.
Operational and analytical workloads
Direct access where appropriate; replicas or dedicated sources where analysis needs to be separated from production processes. Capacity is validated against your workload.
Private and local AI
Configurable AI endpoints, including compatible models on private or local infrastructure. We choose where AI runs based on your data, requirements and expected performance.
Permissions, audit and traceability
Roles and access scopes, user identities and operation logs. Controls are configured around your project’s architecture and processes.
One connection, more ways to work
Use ADA
where you already work.
In your business app, your chat or your AI assistant. ADA connects information and actions to the channels you choose for yourself and your team.
Connect your AI to your data
Claude · ChatGPT · Your AI
Use the assistant you already know to find information and request actions on business data. ADA’s MCP connectors provide the connection, with access and tools configured for your project.
Your assistantADAData and actions
Integrated
Requests, documents and updates connected to your work, straight from your inbox.
Integrated
Telegram
Look up information and run enabled actions directly in your conversation with ADA.
Integrated
Record a new job, check your appointments or find a customer’s details. Just message ADA on WhatsApp.
Questions before we start.
Good to know.
Do we need to replace our existing systems?
No. ADA can connect to existing databases and services alongside your backoffice. Its own application provides an additional operational interface to search and manage exposed entities, while ERP, CRM and other applications continue in their roles.
Is the backoffice really generated from the database?
ADA uses the data model and its relationships to generate records, forms and access tools. First we configure the connection, exposed entities and access rules. Specialised business logic and interfaces are added as modules, so common functionality does not need to be built from scratch.
Can we connect Claude or ChatGPT directly?
Yes. ADA’s MCP server exposes tools for data and enabled actions. We configure the connector in your chosen AI client, authentication and project access. APIs also support integration with internal chatbots and tools.
Can AI run on our infrastructure?
Yes, with compatible models and endpoints. ADA supports configurable AI providers and endpoints, including private or local infrastructure. We assess the model, required resources and response quality for your use case: capabilities differ between models.
How do you handle access, writes and production workloads?
We start with an explicit scope: sources, users, actions and expected load. We configure privileges, confirmations and logging, and assess read-only access or replicas for analytics. Writes go through enabled actions and process rules.
Let’s make it concrete.
Start with a process.
Bring AI into it.
Start with your data, processes and goals. We define the architecture, integrations and a first use case to validate against your workload.