AI and intelligent agents
Smart assistants, AI agents, natural-language processing and connecting AI models to enterprise systems.
AKAM DATA · RESEARCH & DEVELOPMENT
We don’t just follow technology; we develop it for real problems.
Akam Data’s R&D unit is where software, accounting, AI and business-management knowledge meet: problems become research opportunities, ideas become prototypes, and successful solutions become products.
Strategic focus: Making financial and enterprise software intelligent
- 7strategic R&D areas
- 4specialised labs
- 6stages from idea to product
- 20+years of experience in technology and software
A management view of innovation
R&D: the engine of Akam Data’s future products
R&D is not just a technical unit; it is a strategic capability for choosing the right opportunities, reducing the risk of investing in ideas and building a lasting competitive advantage.
Our priority is problems close to customers’ real experience, especially in accounting, financial management, sales, warehousing, production and organisational processes. Every research output must be measurable, and if its value is proven, it follows the path to becoming a product.
- Problem-driven, needs-based
- Fast, low-cost prototyping
- Business value assessment
- Security and quality from day one
R&D focus areas
Seven connected tracks that shape the research and development of future products.
FinTech and smarter accounting
Analysing financial documents, finding discrepancies, spotting unusual patterns and supporting finance managers’ decisions.
ERP, CRM and enterprise automation
Integrating finance, sales, warehouse and production processes and developing smart, traceable workflows.
Business intelligence and data analytics
Turning operational data into management dashboards, trend analysis and decision-support tools.
Cloud computing and SaaS products
Multi-tenant architecture, subscription services, secure APIs and scalable infrastructure for cloud software.
Smart industrial technologies
Research on smart manufacturing, the supply chain, sales and distribution, and linking software to industrial operations.
Specialised labs: from idea to an evaluable prototype
The labs are focused research tracks; the R&D activity map is completed as projects progress.
01 · ACCOUNTING INTELLIGENCE LAB
Accounting Intelligence Lab
Detecting discrepancies, analysing documents, identifying duplicate entries and giving managers financial insight, while keeping the human expert in the oversight role.
02 · AI & AGENT LAB
AI and Agents Lab
Building specialised assistants and software agents for defined tasks, with supervision, reporting and access control.
03 · BUSINESS AUTOMATION LAB
Business Automation Lab
Analysing repetitive workflows and designing integrated processes to reduce rework and increase transparency.
04 · DATA & BI LAB
Data and BI Lab
Turning financial and operational data into key indicators, management reports and business-trend analysis.
Innovation at Akam Data: the path from an idea to a product
For us, innovation means an idea that starts from a real problem, is tested step by step and becomes a product only once its value is proven. Every idea sits in one of these six states, and its status is updated as real progress is made.
- 01New ideasIdeas
Suggestions and problems that arrive from customers, teams and the market.
- 02Under reviewResearch
Technical feasibility, user value and risk are assessed.
- 03PrototypePrototype
A small, testable version is built.
- 04In developmentDevelopment
The approved idea is developed to product standards.
- 05Testing and evaluationTesting
Performance, security and user experience are evaluated with real users.
- 06Ready for commercialisationCommercialization
Production, support and launch plans are prepared.
The R&D management process
Each idea goes through a staged path with clear criteria to continue, adjust or stop investment.
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Problem discovery
We define the customer need and the market gap.
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Research and feasibility
We assess technology, cost, risk and potential value.
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Solution design
We set the hypothesis, architecture and success metrics.
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Prototyping
We build a small, testable version.
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Validation
We evaluate performance, security and business value.
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Transfer to product
If approved, a production and launch plan is drawn up.
Proposed project tracks
Examples of topics that can be pursued in the research portfolio; each project’s status is updated with real progress.
RESEARCH TRACK · FINTECH
Smart assistant for analysing financial information
Exploring question-driven analysis of financial data, explaining changes in indicators and flagging items an accountant should review.
AI & AGENTS
A framework for building and managing AI agents
BUSINESS AUTOMATION
Enterprise workflow automation
These are research tracks and proposed ideas; until outputs are recorded and internally approved, they are not finished products or completed projects.
How do we measure R&D success?
The number of ideas alone is not the measure; the quality of validation and the real impact of outputs matter more.
Time to prototypeAverage days from approving an idea to building an MVP
Validation pass rateShare of prototypes that meet technical and user criteria
Impact on customersTime saved, fewer errors or improved satisfaction in real trials
Have a real problem? Let’s research the solution together.
We welcome collaboration with specialists in software, accounting, data and AI, universities, and businesses with a solvable problem.
Frequently asked questions about R&D
What does Akam Data’s R&D unit focus on?
The main focus is AI, smarter accounting, FinTech, ERP and CRM, enterprise automation, data analytics, cloud computing and software security.
Can I propose an idea or problem for research?
Yes. Businesses and specialists can bring their problem or idea to Akam Data for an initial review and feasibility study.
Do all research topics become products?
No. Each topic is decided on after technical and economic review and an assessment of user value; some ideas may be stopped or kept for later.
What is the Accounting Intelligence Lab for?
Studying how AI can analyse financial documents and data, find discrepancies and support decisions; the final decision and financial controls remain with the human expert.