00 / IDLE
SCROLL
10-51 LABS · EST. 2024 · MUMBAI, IN
SECTION / HERO
25,400 mm 12,200 mm ZONE A / MEP ZONE B / STRUCT ZONE C / HVAC ZONE D / ELEC ZONE E / PLBG
AGENTIC AI · CONSTRUCTION INTELLIGENCE · V.2026

Estimate
at the speed
of thought.

Agentic AI construction software for effortless
Estimation and Management.
Purpose-built for MEP contractors in India.
Built by estimators, for estimators.

LAT 19.2183° N · LNG 72.9781° E
FILE · ESTIMATTER-2026-R01
01 / THE PROBLEM

Estimation is where
projects bleed time,
margin & trust.

Across 1,200+ tenders observed, eight compounding frictions turn early-stage estimation into a cost center. We rebuilt the workflow ground-up.

08 compounding frictions · observed across 1,200+ Indian MEP tenders
02 /THE TRANSFORM

From weeks of
spreadsheets →
minutes of clarity.

Three agents. One workflow. Estimatter . ingests raw inputs and returns instant, accurate, smart estimates 92–97% QTO, 96% BOQ mapping accuracy.

STEP 01 / BEFOREINPUT
01

Raw BOQ, unmapped line items.

#DESCRIPTIONQTYRATE
01GI conduit 25mm
02Cu wire 2.5sqmm
03MCB 32A DP
04VRF IDU 3.5TR
STEP 01 / AFTERESTIMATTER

Mapped & priced in seconds.

#DESCRIPTION → SKUQTY₹ RATE
01GI conduit 25mm · Polycab847m182
02Cu 2.5mm · Finolex FR4,200m36
03MCB 32A DP · Legrand24612
04VRF IDU 3.5TR · Daikin1284,200
96%BOQ MAPPING ACCURACY
STEP 02 / BEFOREDRAWING
02

Manual take-off. Ruler & highlighter.

measure?
STEP 02 / AFTERAGENT · QTO

Auto-QTO from drawings.

847.3 m 102.1 m
92–97%QTO ACCURACY
STEP 03 / BEFORETIMELINE
03

3 to 14 days. Per project.

DAY 00 DAY 14 ⬤ manual drag
STEP 03 / AFTERINSTANT

10 – 20 minutes. Any project.

T+00 min T+20 min ⬤ agentic run
×200FASTER THAN MANUAL
STEP 04 / BEFOREPRICING
04

Vendor quotes by email. Stale.

☐ vendor_A_quote_v3_FINAL.xlsx
☐ copy_of_rates_2023.pdf
☐ updated_prices_pls_confirm.msg
STEP 04 / AFTERLIVE PRICING

Live pricing intelligence.

VENDOR₹ TODAYΔ 7D
Polycab182.00-2.1%
Finolex186.50+0.8%
Havells ★178.20-3.4%
03 /THE STACK

24 features.
One agentic spine.

Every capability you'd normally stitch together across spreadsheets, ERPs and chat threads — unified into a single intelligence layer. Drag, scroll, or use arrows.

04 /CASE STUDY

Same output.
A fraction of the cost.

A single estimation pod, scaled four ways — benchmarked against a fully-human team processing the same BOQ volume over 1 month. 

TIER 01 / LIGHT LOAD

20 BOQs
processed

20
500
10,000
1 month
HUMAN TEAM3 MEMBERS
2,10,000
SAVE 52%
1 + ESTIMATTER1 MEMBER + AI
1,00,000
05 / MOAT

A defensible
intelligence layer.

M/01

Dual AI
engine.

Separate engines for extraction & pricing. Cross-checked outputs — no single point of failure.

M/02

Proprietary
dataset.

M/03

Live pricing
network.

Real-time vendor feeds and predictive forecasts — not weekly, not stale.

M/04

System-level
automation.

Not a feature — a workflow OS. PO → GRN → invoice → reconciliation, end to end.

M/05

No workflow
lock-in.

Plug into existing ERPs, export to any format. Credit-based pricing, no subscription trap.

06  /PRICING

Pay per credit.
Never per seat.

500cr
₹ 5,000

1 BOQ
or 250 BOQ lines
or 1 drawing
1,200cr
₹ 10,000

2 BOQs
or 600 BOQ lines
or 3 drawings
3,500cr
₹ 25,000

4 BOQs
or 1,750 BOQ lines
or 9 drawings
20,000cr
₹ 1,00,000

22 BOQs
or 10,000 BOQ lines
or 25 drawings
1 BOQ = 500 LINE ITEMS MAX
07/ THE TEAM

Meet the Team.

Karanjeev Duggal
Karanjeev Duggal
Chief Executive Officer
(CEO)
Rishabh Srivastava
Rishabh Srivastava
Chief Technology Officer
(CTO)
AI Agent
Chat GPT
Chief Operating Officer
(COO)
Compute cluster
Apple Mac mini
18 Workforce
Team Agents
Team Agents
6 Team Members