Data Analytics

AIGard turns operational data into clear answers and decisions. We build the analytics layer, metrics and reporting your teams use every day.

The work typically covers:

• Metric and KPI definition
• Analytics data models
• Customer, product and operational analytics
• Self-serve reporting
• Embedded analytics in products
• Training for business users

Data Analytics is usually the right investment in one or more of these situations:

• Leadership lacks a reliable view of performance
• Analysts spend their time assembling data
• You want analytics inside your product
• Different teams define the same metric differently

On a 30-minute scoping call we confirm whether it fits your case and recommend a team shape and first milestones.

Yes, AIGard works with the BI tool you already have, including Tableau, Power BI and others. Our focus is the data model underneath it.

The data model is where metrics are defined, and it is often where different teams' definitions of the same metric diverge. With consistent definitions and a sound analytics model in place, your existing tool can provide the self-serve reporting your teams use every day.

AIGard delivers a first set of agreed metrics early in a data analytics engagement, then expands the dashboards iteratively.

The exact timing depends on the state of your data and the metrics you choose to prioritize. The scoping conversation and written proposal define that first set, and regular demos let your teams review each addition as it is built.

With the decisions the business needs to make, then the data required to support them.

We assess your sources, quality and existing platforms first, and tell you plainly what your data can and cannot support before recommending an architecture.

PII masking, encryption and audit logging are built into data work, and engineers operate inside your environment under least-privilege access.

Data-handling requirements are agreed during scoping and checked before release.

For Data Analytics, AIGard engineers typically work with Snowflake, BigQuery, dbt, Tableau, Power BI and Python.

The stack is selected to fit the systems you already run, and engineers are matched to it before they join.

Data Analytics is available through any of AIGard’s three engagement models: staff augmentation, where engineers join your team; a dedicated team that runs the workstream; or software outsourcing, where AIGard delivers a defined project.

The choice depends on how much of the delivery you want to manage, and it can change later under the same agreement.

Engineers typically start within two to four weeks of the scoping call. The exact date depends on the roles, seniority and number of people required.

We confirm a realistic start date in writing before you commit, and you meet the proposed engineers before work begins.

AIGard engineers typically cost 30–50% less than the fully loaded cost of a comparable US-based hire, with no recruiting fees, benefits overhead or insurance costs on your side.

The figure for a specific engagement depends on the model, the roles, the seniority mix and the size of the team. We issue a written proposal after the scoping call, so the commercial terms are agreed before any work starts.

NDAs are signed before any access is given, and engineers work inside your environment under least-privilege access, with permissions limited to their responsibilities.

Access is reviewed as roles change and removed when work ends. Our practices align with ISO 27001, SOC 2, GDPR and HIPAA, with PII masking, encryption and audit logging built into data work. We review your access policies, data-handling needs and vendor requirements during scoping.

You do. Intellectual property assignment is written into every contract, in every engagement model.

That covers source code, designs, documentation, data, models and prompts produced for you. Third-party components and their licenses are identified, so ownership is clear at handover.