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When data can’t be trusted, everything slows down. Teams double-check numbers, argue over definitions, and spend more time preparing reports than using them.
Majoris Inc builds data systems that stay reliable: stable pipelines, sensible data models, decision-first dashboards, and AI-ready foundations like vector databases and knowledge bases. One source of truth. Clear answers. Faster moves.
What we build inside this service
Each module below is delivered as a real build service. Pick one, or combine a few depending on your data maturity and goals.
Data Pipelines
We build pipelines that move data from CRMs, apps, databases, and analytics tools into a dependable destination with monitoring, retries, and clean transformations.
- Teams pulling data from multiple tools
- Operations and reporting automation
- Reducing manual spreadsheet work
- Fewer broken reports
- Consistent daily/weekly data
- Cleaner foundation for dashboards
Vector Database Integration
We integrate vector databases for AI retrieval workflows like RAG, internal search, knowledge assistants, and content intelligence. Optimized embeddings, fast retrieval, and proper access control included.
- RAG chatbots and internal copilots
- Search across docs, tickets, and policies
- AI support agents with reliable retrieval
- Better answer accuracy
- Faster retrieval response time
- Lower hallucination risk
Knowledge Base Setup
We organize and structure your internal docs, SOPs, FAQs, and product knowledge so humans and AI can reliably find the right information with permissions and versioning.
- Support and ops documentation
- Growing teams needing consistency
- Preparing knowledge for AI retrieval
- Less repeated questions internally
- Faster onboarding
- Strong base for AI assistants
AI Search Systems
We build AI-powered search experiences for internal tools, customer portals, or knowledge hubs, combining semantic retrieval with practical UX so people actually use it.
- Large internal documentation libraries
- Customer help centers and portals
- Product search and content discovery
- Faster information discovery
- Fewer support tickets
- Better self-serve experience
Analytics Dashboards
We design dashboards around decisions: what’s changing, what’s risky, what’s improving, and what needs action. Built with clean definitions and reliable inputs.
- Leadership and ops reporting
- Marketing and sales performance tracking
- Product and customer analytics
- Clear KPIs that align teams
- Faster decisions with less debate
- Early alerts on anomalies
Reporting & Insights
We automate recurring reporting and deliver insights in a way people actually read. Scheduled summaries, anomaly alerts, and narrative-style reporting when needed.
- Weekly reporting and performance reviews
- Teams tired of manual slide decks
- Early warnings and data monitoring
- Less time wasted on reporting
- Faster detection of issues
- More confident planning
Data Modeling
We design data models that make metrics consistent across teams. Clean definitions, scalable schema design, and structured layers that support analytics and AI use cases.
- Companies scaling reporting across teams
- Fixing inconsistent KPIs
- Preparing for warehouse or AI search
- Aligned metrics and reporting
- Cleaner dashboards
- Less confusion and rework
ETL Automation
We automate ETL workflows with logging, retries, scheduling, and alerting so your data systems run reliably. Clean transformations included, not “quick scripts”.
- Replacing manual exports and imports
- Automated data syncing across tools
- Operational reporting at scale
- More reliable data refresh
- Less human error
- Auditable data processes
How we build data systems that stay reliable
step 01
Audit + definitions
We map sources, access, reliability, and define KPIs properly so teams stop arguing over numbers.
step 02
Pipelines + models
We build pipelines and data models with monitoring and validation so issues get caught early, not during reporting.
step 03
Dashboards + intelligence layer
We ship dashboards, automated reporting, and AI-ready retrieval layers so your systems become smarter over time.
Built for clarity, trust, and action
Consistent metrics
One definition per KPI. Dashboards and reports align across teams and tools.
AI-ready foundation
Knowledge, search, retrieval, and vector layers that power real AI systems, not demos.
Faster decisions
Less debate, more action. Teams trust the numbers and move faster.
FAQs about Data & Intelligence
These are the questions teams ask before investing in data infrastructure, dashboards, and AI-ready systems.
Yes. We connect and normalize data across CRMs, analytics tools, databases, product platforms, spreadsheets, and internal systems. We focus on reliability, not tool switching.
Yes. That’s one of the main reasons teams invest in this service. We build with AI retrieval in mind: structured knowledge, clean permissions, and vector database layers where needed.
It depends on scope and data complexity. We usually start with the highest-impact KPI or workflow, deliver a working version fast, and then scale in milestones.
Yes. We standardize definitions, align transformations, and build a single source of truth so metrics stop changing based on which tool someone opens.
Yes. We support monitoring, pipeline fixes, new data sources, dashboard improvements, and ongoing intelligence enhancements as your needs evolve.