Natural language analytics for retail leadership

Services

Data Engineering
NLP

Technology

Python
LLM APIs

Client

TwinFusion

Leaders queried sales performance in plain language with governed access.

Project

TwinFusion leadership needed sales answers in plain language — without exporting CSVs or waiting on analysts.

The sprint delivered governed natural language analytics over curated retail metrics.

Tasks

Define metric catalog and row-level security rules
Build NL-to-SQL with guardrails and query explainability
Ship executive dashboard with saved questions
Document data dictionary for self-serve expansion

KPIs

1. Same-day insights — leadership queries without analyst queue
2. Governed access — every answer respects role-based filters
3. Adoption — weekly active leadership users within 30 days

Project journey

1. Metric design
Workshops with finance and merchandising on canonical definitions.
2. Assistant build
Guardrailed NL interface over the metric warehouse.
3. Enablement
Training and playbook for expanding question types safely.

Challenges

TwinFusion needed systems that could scale with operational complexity — replacing manual coordination and disconnected tools that slowed decision-making.

Manual workflows consumed team capacity and introduced errors at scale.
Legacy tooling could not support modern analytics or automation requirements.
Integration gaps between departments created data silos and delayed responses.

Results

Delivered sales analytics ai on schedule with measurable operational improvements
Reduced manual coordination overhead across teams
Integrated with existing systems without big-bang disruption
Documented runbooks and monitoring for sustained operations

Production

Grade delivery

Measurable

Business outcomes

Operated

Post-launch support