USE CASE · TRADERS & DISTRIBUTORS
Margin truth.
SKU by SKU

Trading lives or dies on margin clarity.
Most traders don't have it.

Your aggregate P&L looks fine. But which SKUs are actually profitable after discounts and returns? Which customers are silently bleeding margin? Which inventory is aging in the warehouse? Today these answers live across Tally, your CRM, and your stock module - and pulling them out takes weeks. We read all three at once and surface the truth.

3 wks
Average time to live production
0
Spreadsheet exports required
9.2s
Average query response
kolossus · trading stackALL READY
Tally Prime / Tally.ERP 9ODBC
CRM (Sell.do · Zoho · custom)API
Multi-warehouse stockDB
Excel price & discount sheetsFILES
E-com / MT channel dataFEED
WhatsApp order intakePARSE
6 / 6 sources connectedREADY · 9.2s avg
Why this page exists

Aggregate P&L is the most dangerous report in trading. It hides everything that matters.

Your accountant prints a monthly P&L. Revenue is up. Gross margin looks healthy. You sleep fine.

Then six months later you discover that your top three customers were buying low-margin SKUs the whole time, your highest-margin items were sitting unsold in Bombay warehouse, and one channel was eating ₹40 lakh in returns nobody flagged. The aggregate hid all of it.

We built Kolossus to surface what aggregate P&L hides - SKU-level margin, customer-level margin, channel-level margin, dead stock by warehouse and age, customer aging by segment. Same data you already have, just stitched across systems and queryable in seconds.

AGGREGATE P&L PATH
What you find out too late
  • xMonthly summary hides SKU + customer leakage
  • xDead stock found at year-end audit
  • xBad-debt customers caught after they're gone
Outcome · ₹40L returns spotted six months later
VS
KOLOSSUS PATH
What you see this Monday
  • +SKU + customer margin visible weekly
  • +Aging stock flagged before it dies
  • +Customer slippage caught at first sign
Outcome · live in 21 days
What you'll actually use

Three reports for every Monday morning.
Now you can.

Each example crosses systems - sales from your CRM, costs and discounts from Tally, stock levels from your warehouse module. One query, full truth.

01 · SKU + CUSTOMER MARGIN
Monday morning. You want to know which SKU + customer combinations are actually losing money - after discounts, returns and freight.
8.6s
CRM × TALLY · Q3 · 2,418 combinations12 negative
12losing money · -₹28.4L net
SKU × CUSTOMERLISTNETNET MARGIN%
SKU-1108PATEL STORES · MT₹92-₹4.2L
-6.8%
SKU-3345MODERN BAZAAR · MT₹64-₹2.8L
-4.1%
SKU-1041SHARMA DIST · DIST₹210+₹3.1L
+11.4%
9 more combinations · -₹8.0LDRIVER · DISCOUNT STACKING
-₹28.4Lnet negative
47%from one customer
8.6sto surface
What happens next
04 STEPS
  • 01Drills into discount stacking rules driving the loss
  • 02Flags customer-specific deals for renegotiation
  • 03Suggests SKU + customer combos to deprioritize
  • 04Sends weekly margin watchlist to sales head
Excel pivots · usually skipped8.6 SECONDS
02 · DEAD STOCK IDENTIFICATION
End of quarter. You need to know which SKUs are silently aging in your warehouses - before they become unsellable.
5.2s
STOCK × SALES · 4 warehouses · 2,140 SKUs scanned147 idle 90+ days
₹62.4Lstuck · 147 SKUs · ₹22.1L past 180d
147idle 90+ days
₹62.4Lcapital stuck
₹22.1Lpast 180 days
0-90d90-180d180-365d365d+
Mumbai WH42 SKUs idle
₹28.6L
Ahmedabad WH38 SKUs idle
₹19.8L
Bangalore WH31 SKUs idle
₹9.4L
Delhi WH36 SKUs idle
₹4.6L
cross-warehouse age scanTOTAL · ₹62.4L
₹62.4Lcapital stuck
147SKUs · 90d+ idle
5.2sto flag
What happens next
04 STEPS
  • 01Suggests inter-warehouse transfers for SKUs selling elsewhere
  • 02Flags candidates for clearance pricing
  • 03Tracks 180+ day SKUs for write-off decisioning
  • 04Notifies category heads via WhatsApp summary
Quarterly Excel · usually delayed5.2s · RUNS WEEKLY
03 · CUSTOMER AGING BY SEGMENT
Receivables review. You need to know which customers are quietly slipping - before they become bad debt - broken down by channel and rep.
7.1s
TALLY × CRM · 60d window · 38 customers stretching+38% vs prev qtr
₹84.6Lstretching · 62% in modern trade
38customers stretching
₹84.6Lpast terms
+38%vs prev qtr
Current30d60d90d+
Patel StoresMOD TRADE · R. MEHTA
₹32.4L
Modern BazaarMOD TRADE · R. MEHTA
₹19.9L
Sharma DistributorsDIST · A. PATEL
₹19.8L
Krishna TradingDIRECT B2B · S. RAO
₹12.5L
34 more customers · ₹0 - 5L eachEXPOSURE · ₹84.6L
₹84.6Lpast terms
62%in one channel
7.1sto surface
What happens next
04 STEPS
  • 01Generates collection priority list by channel
  • 02Drafts customer-specific reminders with backup data
  • 03Flags credit limit reviews for stretching accounts
  • 04Sends weekly aging dashboard to sales heads
Tally ledger · channel cut skipped7.1s · RUNS WEEKLY
How we read your trading stack

Most traders run three core systems. Kolossus reads all three together.

Sales lives in your CRM (or your team's heads). Stock lives in your warehouse module or Tally inventory. Cost and tax live in Tally. We read all three and stitch them at query time - without forcing you to consolidate first.

Sell.do · Zoho · SalesforceAPI
Custom CRMsDB
Customer master & SOSYNC
Channel + rep taggingNATIVE
Tally godowns / multi-warehouseDB
SKU master · batch · lot trackingSYNC
E-commerce · MT channel feedsFEED
Tally · cost · returns · GSTODBC
Discount · rebate · scheme laddersPRICE
Multi-GSTIN · multi-stateRECON
The trading specifics

Things generic dashboards miss.
We built around them.

The realities of running a multi-warehouse, multi-channel, multi-discount distribution business. We've already met every one of them.

Discount + rebate stacking
Volume discounts, payment-term discounts, channel rebates, scheme offers - Kolossus reads every layer and shows true net realization per SKU per customer. If discount ladders live in Excel sheets your finance team maintains, we read those too.
Volume slabs +Payment-term +Channel rebates +Scheme offers +Excel ladders +
Multi-warehouse stock
SKU stock visible across all your warehouses simultaneously. Suggests inter-warehouse transfers when one location is dead and another is short.
Channel-wise reporting
Direct B2B, distributor, e-commerce, modern trade - every report segments by channel automatically when channel data exists in your CRM or customer master.
SKU master variations
Same SKU named differently in CRM, Tally, and warehouse module? Kolossus auto-maps variants during the first POC week. Once mapped, queries work across systems transparently.
Hindi + regional languages
Customer names, item descriptions, vendor records in Hindi, Gujarati, Tamil and other Indian languages - handled natively, no translation layer needed.
On-prem Nano LLM
Sensitive customer pricing, exclusive distributor contracts? Deploy Kolossus on-premise via our Nano LLM - runs entirely on your infrastructure. Customer data never leaves the building.
Your first 21 days

Specific days. Specific outcomes. Not a generic "30 days to value" promise.

We've done this enough times across trading and distribution customers to know exactly what week three looks like.

21days to live.

From first connection to your team running Kolossus across Tally, your CRM, and every warehouse module in the business. No generic milestones - every day below has happened with a real trading customer.

DAY 1
Connect
Kolossus connects to your Tally, CRM, and inventory module. Multi-system connection completed in a single onboarding call.
DAY 3
First dashboard live
SKU margin or dead stock - whichever is hurting your business most. Live and queryable.
DAY 7
Write-back configured
Kolossus can mark invoices, schedule payments, update records - under your team’s permission tiers.
DAY 14
Team trained
Each person knows the queries relevant to their role. WhatsApp support channel established.
DAY 21
Production daily-use
Manual workflows for configured use cases stop. Your team works with Kolossus, not around it.
21-day production guarantee · Most teams hit it soonerLIVE BY DAY 21
Trading FAQ

Questions trading and distribution CFOs actually ask.

Most of our trading customers also qualify for /for-tally-users - both pages serve you. The difference is framing.

/for-tally-usersdescribes how we connect to Tally and which Tally-native workflows we automate - Outstanding Receivables, GST Reconciliation, Vendor Payments. It's the right page if your first question is "will this read my Tally cleanly?"

This pagefocuses on the analysis questions specific to trading businesses - SKU margin, dead stock, customer aging by channel - which require crossing Tally with your CRM and inventory module. It's the right page if your first question is "why is my margin slipping and where?"

That's exactly the case Kolossus is built for. Most BI tools surface gross sales and call it a day. We read every discount layer - volume slabs, scheme offers, payment-term incentives, channel-specific rates - and compute true net realization per SKU per customer.

If your discount structures live in Excel sheets your finance team maintains, we read those too.

Yes. Multi-warehouse is the default case for our distributors. Stock levels visible across all locations in one query.

Better - Kolossus actively flags "this SKU is dead in Mumbai but short in Bangalore" and suggests transfers. That's the kind of insight aggregate reports never surface.

Channel data tagged in your CRM or customer master is preserved automatically when channel data exists. Every report can be sliced by channel without manual filtering.

E-commerce returns data, modern trade payment cycles, distributor scheme settlements - Kolossus reads all of these into the same view so margin truth is comparable across channels.

That's almost universal in trading businesses.

During the first POC week, Kolossus surfaces SKU master variants ("ABC-RED-500ML" in CRM vs "ABC RED 500" in Tally) and either auto-maps them confidently or flags ambiguous cases for your team to confirm. Once mapped, queries work across systems transparently.

Yes - full role-based access. Territory or rep data filtered per user. The CFO sees the portfolio. Sales heads see their channel or territory. Reps see their accounts only.

Customer pricing and competitor information can be hidden from specific roles. All access is logged and exportable to your security team.

Annual subscription. Tier depends on number of warehouses, users, query volume, and whether you need on-premise deployment.

Most standard mid-market trading businesses fit our default tier.

POC is free for 14 days on your actual data - no credit card required.

Yes - small finance teams are the strongest fit, not the weakest.

Larger trading houses might already have an analyst pulling Excel reports. Smaller distributors often skip these analyses entirely because nobody has the time. Kolossus replaces the analyst-pulling-Excel pattern, and gives smaller teams the same insights without adding headcount.

NEXT STEP

Ready to see this on your trading data? Two paths from here.

RECOMMENDED
Start a conversation on WhatsApp
Message a co-founder directly. Tell us about your trading business - warehouses, channels, the systems you run, the margin questions you wish you had faster answers to. We'll tell you honestly whether a 14-day POC makes sense for your business.
Start WhatsApp conversation
Founder replies on WhatsApp · Usually within 5 minutes
EXPLORE FIRST
See how the full product works
Read about Kolossus more broadly - the full product overview, how it works across multiple systems, what our customers are doing with it.
Read the product overview

Frequently Asked Questions

How much does Kolossus cost?

Our Growth tier (which covers most of what a 150-500 person business needs) is ₹20,000–30,000/month. That’s ₹2.4–3.6L/year.

Is that expensive? Compared to what? If your finance team spends 8 hours a week on manual Tally reports, that’s ₹2L/year in analyst time alone. And that’s before counting the decisions made on stale data.