Overview Problem Solution Features How It Works Technology Pricing Roadmap Company Request Pilot
$0B Global WMS Market (2026)
0% Target Late-Dispatch Reduction
0 min Median Early Warning Time
₹0 Cr Illustrative ARR at 100 Facilities

Predict warehouse workloads.
Keep dispatch on schedule.

SrehFlow uses AI-powered forecasting and dispatch-risk prediction to give warehouse supervisors time to act — before delays become unavoidable.

Based in Hyderabad, India · CIN: U20299TS2024PTC183065

Dispatch Risk Monitor
Live --:--:-- IST
847 On Track
23 At Risk
4 Critical
Picking
0%
Packing
0%
Staging
0%
Receiving
0%
ORD-4821 Zone B — Packing At Risk 17:42 ETA
ORD-4835 Zone A — Picking On Track 16:15 ETA
ORD-4802 Zone C — Staging Critical 18:01 ETA
ORD-5114 Zone D — Receiving On Track 15:30 ETA

Warehouse teams discover dispatch risks too late

By the time problems surface, recovery options are limited and expensive.

Unpredictable Order Volumes

Incoming orders regularly exceed available picking and packing capacity, creating cascading delays across zones.

Reactive Staffing

Supervisors reassign workers only after queues have already grown, turning small delays into major bottlenecks.

Missed Carrier Cutoffs

Without early warning, teams lack visibility into which orders will miss their dispatch windows until it's too late.

Hidden Bottlenecks

Backlogs in individual zones silently delay downstream operations, compounding across the entire fulfillment chain.

Business impact: Avoidable overtime, delayed shipments, inconsistent service levels, and rising fulfillment costs.

Predict workload pressure before dispatch slips

Forecast and detect

Forecast incoming workload by shift, process, and warehouse zone. Predict orders that may miss carrier cutoffs.

Refresh continuously

Recalculate expected completion times as operating conditions change throughout each shift.

Identify and recommend

Spot picking, packing, and staging bottlenecks. Recommend task priorities and staffing adjustments.

Connect existing systems

Integrate with your warehouse management system while preserving established execution workflows.

Give supervisors time to act while recovery is still possible.
Warehouse logistics operations with workers managing packages and inventory

One workspace for planning and dispatch control

Everything your warehouse team needs to shift from reactive firefighting to proactive operations management.

Workload Forecasting

Estimate order volumes, work minutes, and capacity requirements for upcoming shifts across all warehouse zones.

Dispatch Risk Monitor

Rank orders by predicted lateness, cutoff time, and operational priority to focus supervisor attention where it matters.

Bottleneck Detection

Track queue growth and capacity utilization across receiving, picking, packing, and staging operations.

Resource Planning

Recommend staffing levels by zone, accounting for individual skills, shift availability, and scheduled breaks.

Operational Analytics

Compare planned versus actual performance across shifts and facilities with automated reporting.

Enterprise Security

Tenant isolation, role-based access control, data encryption at rest and in transit, and comprehensive audit logs.

Primary users: Warehouse managers, shift supervisors, fulfillment heads, and 3PL operations teams.

Operational data becomes an actionable shift plan

Five steps from raw warehouse data to supervisor-ready recommendations.

1

Connect

Import orders, scan events, shift schedules, processing rates, and carrier cutoffs through APIs or structured files.

2

Understand Capacity

Estimate processing capacity for each warehouse zone and operation based on historical and live data.

3

Predict Delays

Calculate completion windows and flag orders at risk of missing dispatch before the deadline arrives.

4

Recommend Action

Suggest task reprioritization, order-wave changes, or reassignment of qualified staff to high-pressure zones.

5

Measure Outcomes

Refresh predictions using actual progress and record supervisor decisions for continuous improvement.

Illustrative Scenario

Before a 6:00 PM cutoff, a growing packing queue triggers a recommendation to move qualified staff from a lower-pressure zone, with estimated completion-time impact displayed in real time.

Four components power predictive planning

Purpose-built models that work together to forecast, simulate, and optimise warehouse operations.

SrehForecast

Gradient-boosted models leverage order history, calendar patterns, and live arrival data to predict workload across shifts and zones.

SrehDispatch

Completion-time and lateness models use remaining tasks, queue lengths, and carrier deadlines to flag at-risk orders.

SrehSim

Discrete-event simulation tests how staffing changes or order-priority adjustments would affect warehouse queues before implementation.

SrehPlan

Constrained optimization recommends staffing allocations that respect skills, shift limits, break schedules, and process capacity.

Platform Stack

React + TypeScript interface. Python + FastAPI services. PostgreSQL, object storage, containerized with monitoring and versioned model releases.

Validation

Time-based test splits. Completion-time error measurement. Late-order alert precision tracking. Supervisor approval required before operational changes.

Recurring subscriptions priced per warehouse

Start with Essential visibility and scale to full predictive planning as your operations grow.

Monthly Annual Save 20%
Essential
₹25,000
per warehouse / month

Workload visibility, cutoff monitoring, and standard reports for single-facility operations.

Workload visibility
Cutoff monitoring
Standard reports
Email support
Get Started
Enterprise
₹1,00,000+
per warehouse / month

Advanced integrations, network reporting, and enterprise-grade support for multi-facility operations.

Everything in Growth
Advanced integrations
Multi-facility reporting
Custom SLAs
Dedicated success manager
Contact Sales

Annual contracts. Functionality and volume tiers. Expansion through additional facilities.

A staged path from prototype to commercial deployment

Months 1–3

Discovery & MVP

  • 15 customer interviews
  • Define warehouse event schema
  • Build ingestion, cutoff tracking, supervisor dashboard
  • Establish forecasting baselines
Months 4–6

Pilot Validation

  • Target 3 pilot facilities
  • Add workload forecasts and dispatch-risk alerts
  • Compare predictions with baselines
  • Refine explanations and workflows
Months 7–9

Commercial Launch

  • Launch Essential and Growth plans
  • Convert pilots to annual contracts
  • Add staffing recommendations and simulation
  • Standardise onboarding documentation
Months 10–12

Expansion

  • Target 10 paying facilities
  • Multi-warehouse reporting
  • Model monitoring and access controls
  • Integration partner programme

Built from warehouse operations experience

Company Details

CompanySreh Technologies Private Limited
CINU20299TS2024PTC183065
Status Active
IncorporatedMarch 7, 2024
Age2+ years
LocationAkash Ganga, 4th Floor, Khairatabad, Hyderabad, Telangana 500073

Directors

VB

Vinod Kumar Baid

Director

[email protected]
MJ

Mahip Jain

Director

[email protected]
Team collaboration meeting in a modern office setting
Hyderabad, Telangana, India

Ready to predict your warehouse workloads?

Explore workload forecasting and dispatch-risk prediction for your warehouse. Start with a structured pilot at one facility.

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Akash Ganga, 4th Floor, Khairatabad, Hyderabad 500073 · [email protected] · [email protected]