ai conversational analytics for your data
Ask your data
and decide faster
Aida runs inside your infrastructure and responds as soon as a question appears.
features
Capabilities built
for clarity
Designed to reduce cognitive load and present information in a way that stays stable and predictable.
Minutes to insight
Ask in plain language and receive structured decision-ready outputs with tables, charts, and concise explanations: no SQL or manual preparation required.
All sources, no limits
Maintains a consistent view of entities relationships and metrics across systems so answers rely on a unified model rather than disconnected tables.
Role based access
Applies granular permissions and lineage aware filtering so every answer reflects existing security policies without extra configuration.
Charts tables summaries
Understands context and entities, cites sources, and returns structured answers with charts and next-best actions.
Thinks like your best analyst
Surfaces anomalies patterns and key drivers and gives practical next steps that show what happened why and what should follow.
Collaboration and sharing
Supports shared workspaces and reusable views so teams keep context aligned and move forward with a common understanding.
How it works
How clarity forms
Aida behaves like a system that reorganises itself around your intent. Each step feels immediate and each interaction reveals more context.
Step 1
Connect
Step 2
Understand
Step 3
Decide
Context
Why analytics
breaks today
Modern analytics creates the same set of problems for every organisation. We lived through them ourselves long before building Aida — and they shaped the product from day one.
Slow decisions
Analysts spend most of their time preparing data which forces teams to wait days for answers.
Data silos
Insight is scattered across ERP, CRM spreadsheets, docs, and dashboards with no shared understanding.
Shadow AI
Teams paste internal data into public AI systems because secure on prem alternatives are missing.
70%
Analyst time spent on preparation instead of insight.
40% to 60%
Enterprise data that never becomes part of a decision.
3 to 5 days
Typical waiting time for an ad hoc analysis.
60%
Employees who have used public AI tools with internal company data at least once.
15 to 30 systems
Typical number of active data producing systems in a mid sized to large enterprise.
80%
Business users who say they would make faster decisions with real time insight.
Experience
Typical alternatives
Aida
Deployment
Public SaaS shared tenancy
On prem or private cloud data never leaves your environment
Data coverage
Limited connectors per source caps
Unlimited tables any source class unified entity graph
Access control
Coarse roles partial logging
Native RBAC ABAC SSO SAML OIDC full audit
Query method
Prompt only answers little structure
Any language dialogue cited tables charts recommendations
Reliability
Opaque failures unclear retries
Deterministic pipelines fallbacks source health checks
Transparency
Little to no provenance
Citations query plans lineage surfaced
TCO
Egress usage surprises lock in
Your infra predictable scaling
Case
Monobank.
Conversational analytics
for a fintech unicorn
About
Monobank is one of the fastest growing digital banks in Europe with millions of active customers and a deeply complex operational landscape.
The organisation works with 1000+ data sources ranging from core banking systems to risk engines, fraud pipelines, support platforms, and marketing tools.
Industry
Digital neobank
Scale
Leading European fintech with 7M+ customers
App rating
4.9 on major mobile stores
Daily transactions
Millions processed per day
Link
Data footprint
1000+
Average task time
16h → 30min
Productivity gain
Up to 32×
Users
250+
MAU
47,7%
DAU
4,9%
AIDA is f***ing awesome. Previously, getting answers meant hours of work. Now I just feed it table names, column descriptions, and my question. It gives answers plus extra insights, charts, and hypotheses. For instance, I needed to find companies that stopped paying salaries via us. Libre answered faster than I could find my old script.
Vlad Z.
Product Owner
I use it daily—for finding tables, writing scripts, or gathering data from DB
Lena T.
Marketing Lead
I use AIDA for quick product analytics. With prepped tables, we get results in 5–10 minutes that would’ve taken us two days before. Example: we analyzed product labels vs. catalog listings—super efficient.
Vitalii O.
Product Owner
reliability
Why should trust the result
Every choice made during analysis is documented and visible. Users see how an answer was assembled and why specific data contributed to the result.
Sources and fields included in every result
Generated SQL available for review
Reasoning and assumptions surfaced
Lineage and logs visible throughout the stack
Security
Built for containment
A clear security boundary keeps information contained and predictable. Information stays contained and every request is processed with predictable safeguards.
On prem or private cloud deployment
Single sign on with least privilege access
Encryption in transit and at rest with full audit logs
Private model options or on prem endpoints
Integrations
One connected landscape
All connected systems are treated as one continuous landscape. Data moves seamlessly across sources and answers reflect the full context.
Databases and warehouses
Files and storage
Documents and wikis
APIs and microservices
Applications and ticketing
Business intelligence and metrics
Begin your
Aida journey
Tell us about your environment and decision flow. Aida adapts to complex landscapes and helps teams move faster with confidence.
© Artificial Intelligence Solutions Limited
2025–Future