AI Dashboards & Intelligent Analytics Interfaces

We build dashboards with AI-supported analysis and near real-time data processing that support the analysis and interpretation of product, operational, and customer data — searchable, designed with transparency in mind, and connected directly to your business workflows.

About

We build dashboards with AI-supported analysis and near real-time data processing that support the analysis and interpretation of product, operational, and customer data — searchable, designed with transparency in mind, and connected directly to your business workflows.

Our dashboards are not static charts. We combine machine learning, semantic search, vector retrieval, and predictive models with clean, modern UI to build interactive analytics tools to support data-driven workflows for teams worldwide. From internal BI systems to customer-facing dashboards embedded in your SaaS platform, we architect, design, and implement intelligent data experiences that scale.

Services

What We Deliver

Real-Time Dashboards

  • Live performance metrics
  • Streaming data (events, logs, usage, IoT)
  • Operational dashboards for sales, marketing, or product teams
  • Role-based access and granular permissions
  • Multi-tenant dashboards for SaaS platforms
  • Automated alerts and anomaly detection

AI-Powered Insights

  • Semantic search across your business data
  • "Ask your data" interfaces powered by LLMs
  • Smart summaries, explanations, and insights
  • Conversational analytics (chat over numbers + charts)
  • Automated reporting & PDF generation
  • Insights delivered via email, Slack, or WhatsApp

Data Processing & Warehousing

  • ETL/ELT pipelines
  • Data modeling and transformation (dbt, SQL)
  • Warehouse setup (BigQuery, ClickHouse, PostgreSQL)
  • Supabase & vector stores integration
  • High-volume ingestion with queues and streaming

Predictive & ML-Driven Analytics

  • Forecasting models to support analysis of sales, leads, supply, demand, and churn
  • User behavior scoring
  • Lead qualification and routing
  • Recommendation systems
  • Time-series modeling and anomaly detection
Differentiation

Differentiation from related services

If you primarily need forecasts or scoring models, Predictive Analytics is the right entry point. If you want an operational agent with handoff and tool actions, AI Assistants is the right service. This page focuses on analytics interfaces: dashboards, search, and decision support in product or internal tools.

Why choose

Why Companies Choose Our AI Dashboards

  • Modern TypeScript-based stack (Next.js, React, Supabase, Prisma)
  • Insights designed with transparency and traceability, avoiding unnecessary black-box behavior where possible
  • Data handling designed to align with GDPR requirements and EU-based hosting
  • Performance-first engineering even on large datasets
  • Beautiful, clean, intuitive dashboard UI
  • Enterprise-grade architecture built for scale
  • Deep integration with your internal tools and CRM
Why Companies Choose Our AI Dashboards
When to use

When You Need AI Dashboards

This service is ideal when you need:

A modern BI dashboard your team will actually useAI-powered insights instead of static reportingA centralized analytics layer for company KPIsAn internal or customer-facing analytics toolPredictive metrics for better decision-makingA scalable, maintainable pipeline for product dataTo replace Excel sheets, outdated reports, or messy scripts
Tech stack

Tools & Technologies

Frontend & UI

  • Next.js
  • React
  • Tailwind
  • shadcn/ui
  • D3.js
  • Recharts

Backend & Data Layer

  • Supabase
  • PostgreSQL
  • Prisma
  • ClickHouse
  • BigQuery

ML & AI

  • OpenAI
  • local LLMs
  • embeddings
  • vector DBs
  • Python ML models

Pipelines

  • dbt
  • Airbyte
  • Airflow
  • Kafka/Redpanda
  • queues
  • ETL/ELT

Infrastructure

  • Vercel EU
  • Supabase EU
  • AWS EU
  • Docker
  • CI/CD
Process

Process: How We Build AI Dashboards

01

Step 1 — Discovery & Data Audit

Identify data sources, Assess quality, structure, and gaps, Define KPIs and insight types

02

Step 2 — Data Modeling & Architecture

Warehouse or database setup, ETL/ELT pipelines, Vector search & semantic layers

03

Step 3 — Dashboard & UI Development

Interactive charts & tables, Filters, roles, permissions, Realtime data updates

04

Step 4 — AI Intelligence Layer

Semantic search, Insight summaries, Predictive models, Automated reporting

05

Step 5 — Launch & Optimization

Performance tuning, Access control & security, Ongoing improvements

Examples

Example AI Dashboard Work (Case Studies)

Real-time sales intelligence dashboard for a B2B company. Live metrics, forecasting, and AI-powered insights for sales teams

AI search interface over 2M+ documents. Semantic search and intelligent document retrieval system

Forecasting system for lead generation and revenue planning. Predictive analytics dashboard with ML-driven forecasts

Operational dashboard for a SaaS platform with multi-tenant support. Multi-tenant analytics with role-based access and real-time updates

IoT data analytics with anomaly detection and alerts. Real-time IoT monitoring dashboard with automated anomaly detection

Scope

What you get with AI dashboards

011–2 weeks discovery and data audit
02Outcome: KPI definition + data model + architecture plan + UI scope
03Then: 4–8 weeks build depending on data readiness, embeddings, and multi-tenant needs
FAQ

FAQ

Yes — we build conversational analytics and "chat with your data" interfaces.

Yes — we work with ClickHouse, BigQuery, PostgreSQL, and streaming systems.

Systems are designed to support GDPR-aligned data processing and EU-based hosting, depending on configuration and use case.

Absolutely — we build customer-facing dashboards with role-based access.

Yes — forecasting, scoring, anomaly detection, behavior predictions, and more.

Related Articles

Related Articles

More insights and best practices on this topic

View All Articles

AI dashboards for companies operating production analytics systems. We support organizations with AI-powered dashboards, analytics interfaces, and dashboard development based on the specific technical and regulatory context of each project. All services are delivered individually and depend on system requirements and constraints.