Overview
What Our Data and AI Services Cover
Help to connect, organize and use business data, from the first reports to practical AI.
Types of Work
- Data integration across business systems
- Data quality, governance and ownership
- Business intelligence and automated reporting
- Analytics and forecasting
- AI readiness, adoption and governance
Environments
- Business applications and databases
- Cloud and on-premises data platforms
- Spreadsheets and departmental data sources
Scoped Separately
- Custom AI model development
- Ongoing managed reporting operations
- Software and data platform licences
- Changes to source business applications
Challenges
Challenges We Help Address
The common problems that lead organizations to look for data and AI support.
What We Deliver
Our Data and AI Services
What each service covers and the value it is intended to bring. Engagements include only what you need.
Our Approach
How the Service Is Delivered
A staged approach, agreed with you at the start of each engagement.
Discover and Assess
Understand your decisions, data sources, quality, reporting needs and AI ambitions.
Design and Plan
Define the recommended approach, scope, responsibilities and milestones.
Implement and Integrate
Deliver the agreed work, coordinate dependencies and validate each change.
Validate and Transition
Test the outcome, document the environment and hand over agreed responsibilities.
Optimize and Support
Improve data quality, reports and AI use over time, where included in the engagement.
Use Cases
What You Can Achieve with This Service
The scenarios this service most often supports. Start with the one closest to your situation.
Solutions
Related Solutions
The solutions this service helps deliver, and how it supports each one.
Technology
Technologies We Work With
The technology areas this service works with. Specific platforms and partner status are confirmed per engagement.
Who It Is For
Who This Service Is For
The organizations, teams and environments this service is designed for.
Organization Profile
- Organizations that rely on manual reporting
- Teams that want to use AI with clear rules and controls
Roles and Teams
- Business, finance and operations leaders
- IT, data and analytics teams
- Risk and compliance owners, for AI governance
Environments
- Cloud, on-premises and hybrid data sources
- Business applications such as finance, sales and operations systems
Before You Engage
What to Consider Before Engaging
Having these points ready helps scope the work accurately.
- Business objectives and how success will be measured
- The current environment, dependencies and integration needs
- Security, data handling, governance and compliance requirements
- Access to systems, and who makes decisions on your side
- The main data sources, who owns them and how data may be used
- Engagement models, support hours and pricing
Measuring Performance
Measuring Service Performance
Example measures, not commitments or results achieved by Signisys. Agree a baseline, and keep targets separate from measured results.
Data Quality
The share of records that meet agreed completeness and accuracy checks.
Reporting Cycle Time
The time it takes to produce regular business reports.
Adoption
How many people use the reports and AI tools as intended.
Process Time Saved
Hours saved on manual data and reporting work.
Why Signisys
Why Work with Signisys
How Signisys works, from the first assessment to handover and beyond.
FAQs
Frequently Asked Questions
Common questions about data, analytics and AI services.
What does the service include?
Data integration, data quality and governance, business intelligence and reporting, analytics and AI readiness. Each engagement is scoped to what you need.
Which business needs does it address?
Typical needs include combining data from several systems, replacing manual reports, improving trust in the numbers and starting to use AI safely.
Can the service work with our existing systems?
Yes. The work starts from the data sources and tools you already use.
Where should we start with AI?
With a readiness assessment: the business problems worth solving, the data available, the risks and the rules needed for safe use.
How is success measured?
Agree a baseline for a few measures, such as data quality, reporting time and adoption, and track them over time.
What affects delivery time, scope or cost?
Mainly the number and condition of data sources, the reports and models required, data governance needs and the availability of your teams.
Related Content
Related Outcomes, Industries and Partners
Business outcomes this service supports, and related industry and partner pages.
Industry
Solutions for Manufacturing Industry
Business Outcome
Put AI and Automation to Work
Technology Partner
Claude Solutions and Services
Insights
Data and AI Insights and Guides
Discuss Your Data Goals
Tell us about your goals, current environment and priorities to explore an approach that fits your needs.