GullySystem
Data Engineering and Business Intelligence

Turn Scattered Business Data into Dashboards and Reports Your Management Can Trust

GullySystem consolidates data from your accounting, CRM, ERP and spreadsheets, cleans it, and builds dashboards and scheduled reports — so owners and managers run every meeting on one agreed set of numbers.

  • Built on the systems you already run — Tally, Zoho, Excel, your ERP
  • Every KPI defined in writing and signed off before it appears on a dashboard
  • You own the data model, the pipelines and the source code
gullysystem.live/dashboard Live
Reports Refreshed
Automatically
No manual sheet
Data Checks
1 mismatch flagged
Before it reached the report
Sources Joined
ERP · Store · Tally
One definition
Recent Pipeline RunsLive stream
[06:00] Overnight refreshCompleted
[06:04] Sales vs stock checkMatched
[06:05] Missing branch fileFlagged to owner

We work with distributors, manufacturers, clinics, professional firms, schools and logistics operators across India — consolidating branch and departmental data, rebuilding reporting that has outgrown spreadsheets, and setting up warehouses and dashboards that finance and operations teams open every working day.

The operational challenge

Does Your Monthly Report Take Days to Prepare — and Still Get Argued About in the Meeting?

!

The Monthly Sheet Is Rebuilt From Scratch Every Time

The same exports, the same paste-together, the same twelve steps each month. One month a date range is widened, another month a depot is left out — so this month’s file and last month’s file cannot honestly be compared, and the trend you are reading is partly the assembly work.

!

Both Numbers Are Right, Under Different Definitions

Sales counts an order when it is booked and includes freight; accounts counts it on the invoice date and excludes branch transfers. Nobody is wrong, nobody wrote it down, and the same disagreement resurfaces at every review.

!

One Dealer, Four Codes — So Every Total Is Wrong

When a party or an item exists under several codes, anything grouped by it misleads. Your biggest dealer never reaches the top-customer list, credit exposure looks smaller per code than it is in total, and one slow-moving item looks like three healthy ones.

!

A Total With Nothing Behind It

The report says the Nashik branch is down. It cannot say which dealers stopped ordering or which items caused it, so the meeting ends with "find out and tell me next month" and the same drop repeats before anyone traces it.

!

A Dashboard Nobody Opens Any More

A reporting screen was built once and its sales figure sits a little away from the ledger. Nobody has ever explained the gap, so the screen is quietly treated as indicative and staff went back to their own Excel file.

!

The Month-End Workbook Only One Clerk Can Run

Hidden columns, manual adjustments and links to a file on one desktop. Nobody else can reproduce the output or explain the adjustments, so when that person is on leave the reporting simply stops.

!

The History Is Not Fit for Forecasting

You want demand forecasting or an AI assistant on your data, but item names are inconsistent, dates are stored as text and half the older rows have blank categories.

A dashboard cannot fix any of this on its own. We work on what sits underneath it first — the sources, the definitions and the condition of the data itself.

GullySystem Solution

One Reporting Foundation, Then Dashboards on Top of It

We do not ask you to replace Tally, your ERP or the spreadsheets your team relies on. We read from those sources on a schedule, clean and reconcile what comes out, hold it in a reporting database of your own, and publish dashboards and scheduled reports from that single copy.

Definitions Agreed Before Any Chart

We write down exactly what counts as a sale, an active customer, an overdue invoice and a closed enquiry, get your finance and sales heads to agree, and record it in a data dictionary. Arguments about numbers usually turn out to be arguments about definitions.

A Reporting Database Separate From Daily Operations

Heavy reporting queries run against a warehouse, not against the system your staff use for billing. Reports stay fast, operations stay unaffected, and history is preserved even when a source system overwrites or purges old records.

Refreshes Nobody Has to Remember

Scheduled pipelines pull, clean and load data on their own, dashboards update behind them, and summary reports go out to the people who need them by email or WhatsApp without anyone preparing a file.

Operational ROI

What Changes Once the Data Is in Order

Focus on business value before discussing technology. Here is what your team accomplishes in week one.

One

One Set of Numbers in the Room

Sales, accounts and operations read the same figure for the same period because it comes from the same defined source.

Scheduled

Management Reporting Without the Month-End Scramble

The consolidated view refreshes on the schedule you set, instead of being rebuilt by hand after the books close.

By Role

KPIs That Match Each Person’s Job

The owner sees cash, sales and branch performance. The warehouse head sees ageing and movement. Nobody wades through screens meant for someone else.

Traceable

Every Figure Can Be Traced Back

Click a total and follow it down to the invoices behind it, so a questioned number is settled in the meeting rather than after it.

Clean

A Customer, Item and Vendor Master You Can Rely On

Duplicates merged, codes standardised and missing fields filled, so counts, outstanding and stock values stop being approximate.

AI-Ready

History Prepared for Forecasting and AI

Consistent categories, proper dates and complete records give you a base that demand forecasting, scoring and AI assistants can actually use later.

Scope of service

What This Service Covers

Everything required from operational discovery to production deployment and long-term maintenance.

01

Data Source Inventory and BI Consulting

We list every place a number currently lives — accounting software, ERP, CRM, branch spreadsheets, WhatsApp registers, machine logs — and identify which one should be treated as authoritative for each figure.

02

KPI Definition and Reporting Design

We turn vague requests such as "show me sales performance" into precise, agreed measures with owners, formulas, periods and exclusions written down before anything is built.

03

Data Modelling and Warehouse Design

We design the tables, keys and relationships that let sales, purchase, inventory and ledger data be analysed together, and build the reporting database that holds them.

04

ETL and Synchronisation Pipelines

Scheduled jobs that extract from your systems, apply cleaning and business rules, and load into the warehouse — with incremental updates, failure alerts and a record of every run.

05

Data Cleaning, Deduplication and Master Data

Fuzzy matching for near-duplicate customers and items, standardised codes and units, corrected date and number formats, and a maintained master list your teams work from.

06

Excel-to-System and Database Migration

We take years of operational spreadsheets or an ageing database, resolve the inconsistencies, and move the history into a structured store without losing what happened before the cut-over.

07

Executive and Departmental Dashboards

Owner, finance, sales, inventory and HR views built for the people who use them — plain labels, comparisons against last period, drill-down to the underlying records.

08

Automated and Scheduled Reporting

Daily, weekly and monthly reports generated and delivered on their own, in the format each recipient needs — a PDF for the board, a working file for accounts, a short digest on WhatsApp for branch heads.

09

Real-Time and Conversational Reporting

Live operational screens where the data supports it, and question-and-answer reporting where a manager can type "receivables overdue beyond ninety days for the Pune branch" in plain language instead of hunting through menus.

010

Data Quality, Governance and Access Control

Validation rules that catch bad records at entry, exception reports for what slips through, role-based access so salary or margin data is visible only to the right people, and a documented owner for each dataset.

011

Database Administration and Performance

Indexing, query tuning, backup and restore routines, and monitoring for the reporting database and, where you need it, for the operational databases behind your applications.

012

AI-Readiness Preparation

Structuring, labelling and gap-filling your historical data so it can feed forecasting models, scoring and AI assistants later, instead of discovering at that point that the history is unusable.

Practical applications

Where This Work Pays Off

Real-world business processes we configure and automate.

Distributor With Each Depot in Its Own Books

An FMCG distributor ran a separate accounting company for every depot, so the owner only saw consolidated sales after the accountant merged files mid-month. A nightly pull from each book into one reporting database gives a branch-by-branch comparison of sales, margin and collections before the depots open.

Modular Interiors Firm That Could Not Trace an Enquiry to an Invoice

Showroom walk-ins, portal leads and site enquiries sat in a CRM while orders sat in the ERP, so nobody could say which source actually produced revenue. Joining enquiry records to invoices gives conversion and average order value by source, by designer and by product line, so promotion spend follows the enquiries that become invoices.

Machinery Spares Trader Sitting on Hidden Dead Stock

Stock value looked healthy in total, but slow movers were buried inside it. Ageing buckets by warehouse, last-sold date per item and reorder history exposed the dead lines, changing what the purchase team reorders and what goes into clearance.

Manufacturer Whose Sales Team Chased Payments Blind

The receivables position lived only with accounts, so field staff called customers without knowing what was actually overdue. A receivables dashboard by customer, executive and credit term, with the overdue list pushed out each morning, put collection follow-up in the hands of the people who meet the customer.

Diagnostics Chain Where Revenue Never Matched Test Volume

Test counts came from the lab system, billing from another application, and concessions were recorded on paper, so per-test profitability was guesswork. Reconciling the three sources into one dataset produced reliable test-wise revenue, discount leakage and centre-wise contribution.

School Running on One Clerk’s Master Spreadsheet

Fee collection, transport charges and concessions were tracked in linked workbooks that only one staff member could maintain. Migrating the history into a structured database with defined fields gave the trustees collection status by class and route, and removed the single point of failure.

Audience fit

Is This Service Right for Your Business?

We partner with established businesses that have outgrown manual processes and want reliable systems.

Owners Who Cannot Verify the Figures They Are Given

You receive a report, but you have no way to check it. If asking how a number was arrived at leads to a file only one person can open, the reporting layer is the problem — not the person preparing it.

Finance Teams Closing the Month by Hand

Businesses where consolidation, branch comparison and management reporting are done through copy-paste every month, with the same effort repeated and the same errors recurring.

Multi-Branch and Multi-Company Operations

Groups running separate books, separate stock points or separate legal entities that need a consolidated view without disturbing how each unit records its transactions.

Companies Running Several Disconnected Systems

Accounting in one package, leads in a CRM, stock in another tool and half the operation in spreadsheets — with no way to answer a question that spans two of them.

Businesses Preparing for Forecasting or AI

Organisations that want demand planning, customer scoring or an AI assistant on their own data and need the history cleaned and structured before any of that is realistic.

When You Do Not Need This Yet

If you run one branch on one system and your monthly report is a single export you run yourself in one sitting, a warehouse and pipelines are more than you need. Improve the reports inside that system first. We are happy to say so in a short review rather than sell you a build.

Feature matrix

Enterprise Capabilities in Plain Business Terms

Multi-Source Connectors

Read from accounting software, ERPs, CRMs, SQL databases, spreadsheets and file drops on a schedule.

Incremental Refresh

Pull only what changed since the last run, so refreshes stay quick as history grows.

Deduplication and Matching

Fuzzy matching to merge near-identical customers, vendors and items with a review step before changes apply.

Historical Snapshots

Keep month-end and day-end positions so past reports can be reproduced exactly as they were.

Drill-Down to Source

Move from a headline figure to the transactions that make it up, without leaving the dashboard.

Role-Based Data Access

Restrict by branch, department or row so each user sees only the data their role permits.

Scheduled Distribution

Reports delivered automatically by email or WhatsApp in PDF, Excel or CSV.

Threshold Alerts

Notifications when receivables, stock cover or margin cross the limits you define.

Mobile Dashboards

Readable layouts for owners and field managers checking figures from a phone.

Data Dictionary

A maintained document defining every metric, its formula, its source and who owns it.

Pipeline Monitoring and Logs

Run history, failure alerts and record counts so you know when a refresh did not complete.

Export and Onward Use

Clean datasets available for your auditor, your analyst or another application through files or an API.

Execution roadmap

Our Structured 6-Step Delivery Process

A transparent path from your first conversation to a reliable production release.

01

Data Discovery

We sit with your finance, sales and operations staff and list every source a number comes from today, including the private spreadsheets. From you we need read access or sample exports, and the name of whoever maintains each file. You get a data-source inventory showing what exists, what conflicts and what is missing.

02

KPI and Reporting Plan

We define each metric in writing — formula, period, inclusions, exclusions and owner — and list the dashboards and scheduled reports to be built. This stage ends in a sign-off gate: nothing is built until your finance and sales heads agree the definitions.

03

Data Model and Dashboard Design

We design the warehouse tables and relationships, and lay out each dashboard screen for review before development. You confirm the layouts, the filters and who should be allowed to see what.

04

Pipeline Build and Data Clean-Up

We build the extraction, cleaning and loading jobs and run them over your history. Cleaning needs your judgement, so we send exception lists — duplicate parties, unmapped items, missing categories — and your team decides which record is correct. Those decisions are then applied as rules.

05

Validation and Go-Live

We reconcile the new reports against figures you already trust, such as a closed month’s audited statement or a signed stock statement, and correct any differences. Acceptance is your finance person confirming the numbers tally, after which dashboards are published and schedules switched on.

06

Training, Handover and Support

We train each group of users on their own screens, hand over the data dictionary and administration notes, and continue to monitor pipeline runs, add reports and adjust definitions as your business changes.

Asset handover

What You Receive Upon Project Completion

Everything required to run, maintain, and expand your software without vendor lock-in.

Data-source inventory with authoritative source per figure
Signed-off KPI and metric definitions
Data model and warehouse or reporting database
ETL and synchronisation pipelines with monitoring
Cleaned, deduplicated historical dataset
Executive and departmental dashboards
Scheduled report definitions and distribution lists
Data dictionary and administration documentation
Full source code and repository access
User training sessions and post-launch support
Connected ecosystem

Connects With the Systems You Already Rely On

We build bridges between your software so you don't have to replace functional existing tools.

Accounting and ERP

  • Tally Prime / ERP 9
  • Zoho Books
  • Busy
  • Marg
  • SAP Business One
  • Custom ERPs

CRM and Sales

  • Zoho CRM
  • HubSpot
  • Salesforce
  • Custom CRM databases

Files and Spreadsheets

  • Excel workbooks
  • Google Sheets
  • CSV and SFTP drops
  • Shared drive exports

Databases and Applications

  • MySQL
  • PostgreSQL
  • Microsoft SQL Server
  • MongoDB
  • REST APIs and webhooks
Engineering foundation

Selected for Reliability, Speed, and Longevity

Technology chosen to match your operational scale and long-term maintainability.

Pipelines and Processing

PythonpandasdbtApache AirflowSQL

Databases and Warehouses

PostgreSQLMySQLClickHouseBigQuery

Dashboards and Reporting

MetabaseApache SupersetPower BIGrafanaCustom Next.js dashboards

Cloud and Operations

AWSDigitalOceanDockerScheduled jobs and backups
The GullySystem difference

Why Business Owners Choose GullySystem

Definitions First, Charts Later

We settle what each number means with your own department heads before building anything. It is the step most reporting projects skip, and the reason their dashboards get distrusted.

We Read From Your Systems, We Do Not Destabilise Them

Extraction is read-only and scheduled outside busy hours where possible, so billing, dispatch and data entry carry on at the same speed while reporting is built.

Reconciled Against Something You Already Trust

Every build is validated against a closed period you have already signed off, so the first question in the first review meeting has an answer.

Dashboards for Business People

Screens are written in the language your staff use — party name, bill number, ageing bucket — not in analyst vocabulary that needs a translator.

No Licence Trap

We work with open tooling wherever it fits, so growth in users or data does not trigger a per-seat bill you did not plan for. Where a licensed tool genuinely suits you better, we say so.

Handover You Can Actually Use

You receive the data model, the pipeline code, the dictionary and the administration notes, so another team could take over the work if you ever chose to.

Commercial models

Flexible Engagement Options

Choose an engagement model that matches your operational scope, budget, and timeline.

BI Assessment

Consulting Before Committing

A short engagement that produces the data-source inventory, agreed KPI definitions and a recommended reporting plan — useful whether or not you build with us.

Fixed-Scope Reporting Build

Defined Dashboards and Pipelines

For a clear brief: named sources, an agreed metric list and a defined set of dashboards and scheduled reports, delivered against a fixed scope.

Phase-Wise Rollout

One Department at a Time

Start with the reporting that hurts most — usually receivables or branch sales — prove the numbers reconcile, then extend to inventory, purchase and HR.

Data and Reporting Retainer

Ongoing Engineering Support

Continuous pipeline monitoring, new reports as questions change, data quality clean-up and database administration for teams without an in-house data person.

Common questions

Frequently Asked Questions

Straightforward answers to the questions owners ask before getting started.

Can you pull data from several different systems at once?

Yes — that is the usual starting point. Most projects combine an accounting package such as Tally or Zoho Books, a CRM or order system, and a set of branch spreadsheets. We connect through APIs where a system provides one, through direct database reads where it does not, and through scheduled file exports for the rest. Each source keeps working exactly as it does today.

Can you clean up years of old Excel data?

Yes, and it is a large part of what this service does. We handle inconsistent item and party names, dates stored as text, merged cells, mixed units, blank categories and duplicate rows. Where a value is genuinely ambiguous we do not guess — we send your team an exception list to decide on, then apply those decisions as repeatable rules so the same problem does not return.

Which dashboard tools do you use?

We match the tool to your situation rather than pushing one product. Metabase and Apache Superset suit teams who want to add internal viewers without a per-seat licence for each one. Power BI suits organisations already invested in Microsoft. For owner-facing screens or customer-facing portals we often build a custom dashboard so the layout matches how your business actually reads its numbers. We explain the trade-offs before you choose.

Can reports update on their own, and will that disturb our accounting or ERP system?

They update on their own, and the extraction is designed not to disturb the source. Pipelines run on a schedule you set — nightly, hourly or several times a day depending on the source — and dashboards refresh behind them, with scheduled reports going out to email or WhatsApp without anyone preparing a file. Extraction is read-only, moves only records that changed since the last run, and is scheduled outside peak hours wherever the source allows. Reporting queries then run against the separate warehouse rather than your billing system, which is precisely why we keep the two apart. If a refresh fails, an alert reaches your administrator and us, so a stale figure is noticed instead of being presented as current.

We already have dashboards nobody trusts. Can you fix those instead of rebuilding?

Often, yes. We start by tracing where each figure comes from and testing it against a period you have already closed. Sometimes the fault is a definition nobody agreed on, sometimes a broken join or a stale refresh, and the existing dashboards can be corrected. If the underlying data model cannot support what you need, we will tell you that plainly rather than patch it indefinitely.

What drives the cost of a project like this?

Four things: the number and awkwardness of the data sources, how much cleaning the history needs, how many dashboards and reports you want, and whether a warehouse is required or your existing database is enough. A single-source dashboard set is a modest piece of work. Consolidating multiple branches with years of untidy spreadsheets is not. We give an itemised proposal after the discovery stage, and you can stop after the assessment if you choose.

What decides how long it takes?

Mostly two things that sit on your side: how quickly access to each source is arranged, and how quickly your team settles the KPI definitions and answers the data exception lists. On our side, duration follows the number of pipelines and the state of the history. We deliver in phases so the first useful dashboard is live while the remaining sources are still being connected.

What do you need from us?

Read access or exports from each source system, one person from finance and one from operations who can answer questions about how the business actually records things, decisions on the exception lists during clean-up, and a known-good reference period we can reconcile against. Without a named business owner for definitions, reporting projects stall — so we ask for that at the start.

How is access to sensitive data controlled?

Access is role-based and can be restricted down to the row — a branch manager sees only that branch, a sales executive only their own accounts, salary and margin data only the people you nominate. Data is encrypted in transit and at rest, hosting location is your choice, credentials are held in a secrets store rather than in code, and we sign an NDA before discovery begins.

Do we own the data model, the pipelines and the dashboards?

Yes, entirely — the warehouse, the pipeline code, the dashboard definitions and the documentation. You get repository access and the intellectual property. Nothing is held back to keep you dependent on us, and where the tooling is open source there is no licence you have to keep renewing through us.

Can this data later support forecasting or AI?

Yes, and preparing for it is part of the design. Consistent categories, proper date handling, retained history and a documented model are exactly what demand forecasting, customer scoring and AI assistants need. Many businesses discover at the AI stage that their history is unusable; doing this work first removes that obstacle, and you get reliable reporting in the meantime whether or not you go further.

Will you train our team, and what support is there afterwards?

We train each group on the screens they will actually use, in plain language, with short recorded walkthroughs and a written data dictionary they can refer back to. After launch there is a warranty period, followed by an optional support arrangement covering pipeline monitoring, fixes, new reports and changes to definitions as your business evolves.

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