Your Data Lives in Five Places.Your Decisions Should Come From One.
Custom AI integrations that connect fragmented data sources into unified intelligence. Built for mid-size B2B companies. Delivered in weeks, not months.
Daily-refreshed dashboards. No manual exports. Custom connectors where none exist. Proven on a live construction-company build.
The AI Implementation Gap
Many AI initiatives stall before they reach production. The difference is rarely the technology: it is the implementation strategy, change management and expertise guiding the work.
Stalled Pilots
Proof-of-concepts that never reach production, wasting months of investment and team resources.
Team Resistance
Employees who fear rather than embrace AI, leading to poor adoption and unrealized potential.
Unclear ROI
Difficulty measuring impact and justifying continued AI investment to stakeholders.
Four Ways to Unify Your Data
From a one-week audit to a long-term AI partnership — pick the tier that matches where you are today.
Data Landscape Audit
Custom pricing based on scope — contact for details
- Audit of all current data sources (marketing, sales, ops)
- Platform data availability + API capability mapping
- Off-the-shelf vs. custom connector assessment
- Cost-benefit analysis per potential connection
- 1-page roadmap with implementation priorities
- 1 kickoff call + 2 follow-ups
Single Integration Build
Custom pricing based on scope — contact for details
- Connect 1-2 data sources to a unified dashboard
- Custom connector (1 source max) if needed
- Basic dashboard (3-5 glanceable KPI cards)
- 2 weeks of post-launch support
- Handoff documentation
Full Stack Implementation
Custom pricing based on scope — contact for details
- Connect 3-7 data sources (marketing, sales, ops, analytics)
- Up to 2 custom connectors built from scratch
- Executive dashboard with day/week/month/year comparisons
- AI-powered insights ("here's what's trending")
- Cost-guarded architecture — zero overage exposure
- Shared project workspace, 4 weeks support, team training
AI Partnership (Ongoing)
Custom pricing based on scope — contact for details
- Everything in Full Stack Implementation
- CRM + call tracking integration (full journey loop)
- Quarterly optimization reviews
- New data sources added as you scale (6 months included)
- Dedicated Slack channel for support
- Priority on feature requests
How We Work With B2B Teams
We combine hands-on technical expertise with custom integration engineering to turn scattered data into answers your team can use, without the enterprise bloat.
Practical Methodology
A documented approach: every decision, obstacle and workaround is recorded in a shared project workspace.
Integration Engineering
Custom connectors, authentication and cost-guarded architecture, built for the platforms you actually use.
Documented Delivery
Every decision, obstacle and workaround is recorded in a shared workspace your team can read.
Knowledge Transfer
We train your team to manage and extend automations independently — no vendor lock-in.
Our Proven Process
A structured approach that minimizes risk and maximizes value at every stage.
Discovery
Deep-dive into your business, challenges, and AI readiness assessment.
Strategy
Custom roadmap with prioritized use cases and clear success metrics.
Build
Agile development with continuous feedback and iterative refinement.
Scale
Full deployment with training, support, and optimization.
From Seven Disconnected Tools to One AI Intelligence Hub
This construction company's Unified AI Intelligence Hub is an example of our Full Stack Implementation tier — connecting 7 data sources with custom connectors, building an executive dashboard, and establishing a cost-guarded architecture.
Frequently Asked Questions
Get answers to the most common questions about AI implementation and our services.
Meet the Founder
Ivica Panic — Founder & B2B AI Integration Specialist
We build custom AI integrations for mid-size B2B companies — connecting fragmented data into unified dashboards that executives can actually use.
Not sure where your data stands?
Start with a Data Landscape Audit. One week, one output: a map of your sources, what each could answer if connected, and what it would realistically take to connect them.