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Ada.im

Deep Analysis Pte. Ltd.

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about

Ada.im is an AI data analyst that transforms raw datasets into enterprise-grade reports in minutes. Upload CSV/Excel or connect commerce and ad sources, and the agent cleans data, writes SQL, builds charts, and highlights trends and anomalies with root-cause notes. Generate dashboards and recurring reports for GMV, ads, inventory, and customer insights without manual spreadsheets. Built on an agent architecture, Ada.im turns messy business data into decision-ready visuals and narratives fast.

Features

1

AI report generation from datasets

Upload a dataset and Ada.im produces a professional report automatically: key metrics, trend charts, comparisons, and written takeaways. It handles messy tables, joins, and calculations, then formats the output as a narrative that reads like an analyst brief. Because findings stay tied to fields and filters, you can ask follow-ups, regenerate sections, and reuse the same structure for weekly reviews. This accelerates reporting across sales, marketing, and ops without rebuilding dashboards fast.

2

Data cleaning + SQL automation

Ada.im automates the slow parts of analysis: cleaning inconsistent columns, standardizing formats, and generating SQL for complex questions. Instead of hand-writing queries or wrangling spreadsheets, you describe what you need and the agent produces reproducible logic. This reduces errors, speeds iteration, and keeps transformations consistent across reports. Teams can move from raw exports to reliable, structured analysis without a dedicated data engineer for every request.

3

Anomaly detection with explanations

Reports don’t just summarize—they flag anomalies and explain likely causes. Ada.im highlights spikes, drops, and outliers, then proposes root-cause hypotheses based on correlated fields and time windows. This helps teams spot risks and opportunities early, like GMV shifts, ad channel changes, pricing moves, or inventory issues. Drill into segments, compare periods, and turn findings into next actions without manual chart hunting, endless filters, or guesswork.

4

Ecommerce and marketplace connectors

Connect common commerce and marketplace sources to automate recurring intelligence. Ada.im supports workflows like daily sales reporting, ad channel analysis, competitor monitoring, and customer insights across platforms such as Shopify and major marketplaces. Once connected, it can generate scheduled reports and dashboards, keeping stakeholders aligned without exporting CSVs every day. This makes analytics practical for lean teams running multiple channels and regions.

5

Chat-driven dashboards and follow-ups

Use chat to refine questions, change date ranges, add breakdowns, or request new visuals. Ada.im keeps context from the dataset and prior reports, so follow-ups are fast and consistent. Turn a one-off analysis into a repeatable dashboard, then refresh it when new data arrives. This reduces tool switching and makes analytics accessible to non-technical teammates while still producing outputs solid enough for leadership reviews and weekly WBRs. Share export charts and keep decisions traceable.

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Recomended For

Ecommerce operators, marketers, and analysts who need faster reporting from messy exports and multi-channel data. Ideal for Shopify sellers, marketplace brands, and growth teams tracking ads, GMV, conversion, and CAC across channels. Useful for ops leads watching inventory and customer trends, and for startups that lack dedicated BI resources but still need executive-ready dashboards, daily briefs, and recurring reports with clear explanations and visuals.

What it solved

Replaces manual spreadsheets, ad-hoc SQL, and slow reporting cycles with an agent that cleans data, builds charts, and writes the story. It solves the bottleneck of turning exports into decision-ready reports, and reduces errors from inconsistent transformations. With anomaly highlights and chat-based follow-ups, teams move from raw data to insights faster and can repeat the same analysis daily or weekly without rebuilding dashboards from scratch.

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