Services

Nine services, mapped to the logistics value chain.

Logistics businesses don't buy "data and AI" — they buy yield they can see by lane, containers that move on time, trucks that don't come back empty, filings that don't hold the cargo, carrier invoices that are checked before they are paid, and shippers who hear about a delay first. Below, each SCIKIQ service line is mapped to the domains where it does that work — for forwarders and NVOCCs, contract-logistics providers, express and road carriers, and shippers in India and on global trade lanes — with the use cases, the KPIs it moves and the accelerators behind it.

See the value-chain map How we add value, by domain Find your service by role
Chapter 2 · Services on the value chain

Where each service line works on the logistics value chain

Read across a row to see where a service line leads and where it supports. Read down a column to see the team a logistics business gets in that domain. Select any domain to see use cases, the KPIs we help move and the working accelerators.

9
Service lines
8
Value-chain domains
17
Lead roles across the map
35
Supporting roles across the map
Leads the work Supports Hover a dot for detail · select a domain to explore it
01 · Advise
Data & AI StrategyStrategy
Data Governance, Trade & Privacy ComplianceGovernance
02 · Build
Data Engineering & Platform ModernisationData platform
AI & Agentic EngineeringAI & agents
03 · Transform
Freight Forwarding, NVOCC & Trade ComplianceFreight & trade
Contract Logistics & WarehousingWarehousing
Road Freight, Express & Last-MileRoad & last mile
Commercial Excellence, Pricing & VisibilityCommercial
04 · Run
Managed Services: DataOps, MLOps & AgentOpsManaged
Service lines engaged 7 6 6 6 7 4 9 7

The mapping shows where each service line typically leads or supports; every engagement is scoped to the business. The value chain itself is explained on the overview.

How we add value

Domain by domain: from data to a measurable outcome

Each domain follows the same path — source data, a governed data product, AI and agents, an outcome the business measures. KPIs are the measures we help you move and track; we agree targets with you, we don't promise them in advance.

Domain 1 of 8

Freight forwarding, NVOCC & trade lanes

Rates move weekly, consolidation and space are planned across many systems, and yield by trade lane is known only at month-end.

Data
Quotes, bookings, schedules & milestones
Data product
Trade-lane & shipment data product
AI & agents
Yield, consolidation & quote agents
Outcome
Fuller boxes, better-priced lanes

Logistics use cases

  • Quote-to-booking conversion and win/loss signals
  • Trade-lane yield and space utilisation
  • Consolidation planning across lanes
  • Rate and surcharge drift monitoring

KPIs we help you move

Yield per TEU / CBMQuote-to-booking conversionSpace utilisationLane margin

Named measures, not promised results. Baselines and targets are set with you in the assessment.

See it working Trade-Lane Intelligence 360
Domain 2 of 8

Road freight & fleet

Trips are planned on the phone, empty return legs eat margin, and tolls, fuel and detention are reconciled long after the truck has gone.

Data
Trips, telematics, FASTag & e-way bills
Data product
Trip & vehicle data product
AI & agents
Load-matching, ETA & trip-cost agents
Outcome
Fewer empty kilometres

Logistics use cases

  • Load matching and back-haul planning
  • ETA prediction from telematics and halts
  • Trip-cost reconciliation: tolls, fuel, detention
  • Driver and vehicle safety signals

KPIs we help you move

Empty-km shareOn-time deliveryCost per kmVehicle utilisation

Named measures, not promised results. Baselines and targets are set with you in the assessment.

See it working Control Tower
Domain 3 of 8

Rail, ports, CFS & ICD

Containers wait at ports, CFSs and inland depots while space, equipment and paperwork are lined up, and dwell is explained after the fact.

Data
Terminal, CFS, rail & yard data
Data product
Container & facility data product
AI & agents
Dwell, congestion & space agents
Outcome
Boxes that move on time

Logistics use cases

  • Live container visibility by origin and destination
  • Dwell-time and congestion prediction
  • Space and equipment utilisation
  • CFS revenue, TEU and market-share analytics

KPIs we help you move

Container dwell timeTEU throughputSpace utilisationRevenue per TEU

Named measures, not promised results. Baselines and targets are set with you in the assessment.

See it working Trade-Lane Intelligence 360
Domain 4 of 8

Contract logistics & warehousing

Multi-client warehouses run to different SLAs, labour and space are planned site by site, and billing lags the work done.

Data
WMS, labour, SLA & billing data
Data product
Site & client data product
AI & agents
Labour, SLA & billing agents
Outcome
SLAs met, work billed

Logistics use cases

  • Labour and slotting optimisation
  • SLA-breach prediction
  • Inventory-accuracy and shrinkage signals
  • Activity-based billing checks

KPIs we help you move

SLA adherenceOrders per labour hourInventory accuracyUnbilled activity

Named measures, not promised results. Baselines and targets are set with you in the assessment.

See it working Revenue Assurance Control Tower
Domain 5 of 8

Express & last-mile delivery

First-attempt failures, returns and COD remittances decide the margin, and every client wants live tracking and proof.

Data
AWBs, scans, attempts, returns & COD
Data product
Shipment & delivery data product
AI & agents
Delivery-success, NDR & COD agents
Outcome
Delivered first time

Logistics use cases

  • Delivery-success prediction and NDR classification
  • Route and hub-capacity planning for peaks
  • Return-to-origin and fraud-risk signals
  • COD remittance reconciliation

KPIs we help you move

First-attempt delivery rateRTO rateCOD remittance cycleCost per shipment

Named measures, not promised results. Baselines and targets are set with you in the assessment.

See it working CLARION
Domain 6 of 8

Customs, trade & compliance

Shipping bills, bills of entry, invoices and licences are keyed by hand, and one mismatch holds the cargo.

Data
Filings, invoices, HS codes & lists
Data product
Trade-document data product
AI & agents
Extraction, classification & screening agents
Outcome
Clean filings, fewer holds

Logistics use cases

  • Document extraction from trade documents
  • HS-classification suggestions with reasoning
  • Pre-filing mismatch checks
  • Denied-party and sanctions screening

KPIs we help you move

Filing error rateClearance timeDocuments per executive per dayHolds and queries

Named measures, not promised results. Baselines and targets are set with you in the assessment.

See it working Data Governance Hub
Domain 7 of 8

Shipper supply chain & control tower

Shippers get a portal per provider, emails for exceptions and a weekly spreadsheet that is already out of date.

Data
Orders, milestones, inventory & PODs
Data product
End-to-end shipment data product
AI & agents
Delay-prediction & update agents
Outcome
Customers informed before they ask

Logistics use cases

  • End-to-end order and shipment tracking
  • Delay prediction with customer impact
  • Self-service shipper portal
  • Carrier and partner scorecards

KPIs we help you move

Shipper-portal adoptionProactive alert shareException resolution timeCustomer retention

Named measures, not promised results. Baselines and targets are set with you in the assessment.

See it working Field Sales & Customer Visibility Control Tower
Domain 8 of 8

Pricing, sales & finance

Sales quote from spreadsheets, carrier invoices arrive late, and margin by lane, customer or job is seen only after the close.

Data
CRM, quotes, carrier invoices & GL
Data product
Commercial & margin data product
AI & agents
Sales, freight-audit & commentary agents
Outcome
Margin you can act on

Logistics use cases

  • Field-sales next-best-action
  • Carrier-invoice and freight-audit matching
  • Job- and lane-level profitability with AI commentary
  • Group, capex and treasury views

KPIs we help you move

Job marginCarrier-invoice exceptionsDays to closeSales productivity

Named measures, not promised results. Baselines and targets are set with you in the assessment.

See it working Group Executive Intelligence CLARION COMPASS
Find your service

Start from your role

Each service line has a clear owner on the client side. Pick yours to jump to the services most teams like yours start with.

CEO / COO
Chief Executive & Chief Operating Officer
Freight
Head of freight, trade lanes & customs
Warehousing
Head of contract logistics & warehousing
CFO
Chief Financial Officer
CIO / CDO
Chief Information & Chief Data Officer
Sales
Head of sales & key accounts
01

Advise

Set direction, make the business case and put the rules in place that data and AI must meet.

Advise · Service line

Data & AI Strategy

ForCEO / COOCIO / CDOCFO
On the value chainForwarding & NVOCCRoad & fleetPorts, CFS & ICDWarehousing & 3PLExpress & last mileVisibility & control towerPricing, sales & finance

The client problem

Pilots multiply across countries, product lines and business units, but few reach production. There is no shared, evidence-based view of where the business stands on data and AI, which use cases pay back, or who owns them.

Outcomes

  • A maturity baseline across 12 capability layers and five stages, scored on evidence rather than opinion
  • A prioritised roadmap of use cases across forwarding, warehousing, delivery, customs and finance, with a business case for each
  • An AI operating model that works across countries, entities and business units

What we do

  • Data & AI maturity assessment
  • AI strategy & use-case prioritisation
  • Lane, customer and entity P&L analytics
  • AI operating model & centre of excellence design

Typical engagements

  • AssessmentMaturity assessment and roadmap
  • Pilot · 30-45 daysProve the top-ranked use case on your data
  • BuildRoadmap delivered through our Build and Transform services
  • Managed runValue tracking and roadmap refresh

Delivered with

Maturity assessment Group Executive Intelligence Value calculator
Advise · Service line

Data Governance, Trade & Privacy Compliance

ForCDOHead of compliance / customsCFO
On the value chainForwarding & NVOCCExpress & last mileCustoms & tradeVisibility & control towerPricing, sales & finance

The client problem

Customer, location, port and partner masters differ by system and country. Every movement carries e-way bills, GST records and customs filings, the DPDP Act 2023 governs consignee and driver data, and AI adds a new layer to govern.

Outcomes

  • Golden records for customers, locations, ports, carriers and agents
  • Customs, GST and e-way bill records joined to the shipment, with lineage
  • AI and agent governance: policy, approvals, evaluation and a kill switch

What we do

  • Customer, location & partner master-data management
  • Trade-document and filing lineage (customs, GST, e-way bills)
  • Denied-party & sanctions screening evidence
  • DPDP consent & data-handling controls
  • Metadata catalogue & AI & agent governance

Typical engagements

  • AssessmentMaster-data and compliance-data gap review
  • Pilot · 30-45 daysGolden record and DQ rules for one domain
  • BuildMDM, lineage and catalogue across countries and entities
  • Managed runOngoing DQ monitoring and stewardship

Delivered with

Data Governance Hub SCIKIQ Data Fabric Agent governance
02

Build

Engineer the data platforms and the AI that runs on them, with governance built in.

Build · Service line

Data Engineering & Platform Modernisation

ForCIOCDO
On the value chainForwarding & NVOCCRoad & fleetPorts, CFS & ICDWarehousing & 3PLExpress & last mileCustoms & tradeVisibility & control towerPricing, sales & finance

The client problem

Booking, TMS, WMS, terminal, customs and finance systems run by region and data centre, with dozens of non-standard sources and hundreds of operational reports. Every new question starts with another extract.

Outcomes

  • One governed, cloud-agnostic data lake for logistics data on Azure, AWS or hybrid
  • Pipelines from booking, TMS, WMS, terminal, customs and ERP systems with lineage from source
  • A standard KPI layer so volume, yield, TEU and revenue mean the same everywhere

What we do

  • Pipelines, batch & streaming (milestones, telematics, scans)
  • Booking, TMS, WMS, terminal & customs connectors
  • Logistics data models, KPI layer & ontology
  • Lakehouse / warehouse on Azure or AWS
  • Infrastructure as Code & legacy modernisation

Typical engagements

  • AssessmentData estate and target-architecture review
  • Pilot · 30-45 daysConnect and curate priority sources end to end
  • BuildPlatform build in sprints, tested with real data
  • Managed runDataOps under agreed SLAs

Delivered with

SCIKIQ Data Fabric 268 data sources Trade-Lane Intelligence 360
Build · Service line

AI & Agentic Engineering

ForCIOCOOHead of customer service
On the value chainForwarding & NVOCCRoad & fleetPorts, CFS & ICDWarehousing & 3PLExpress & last mileCustoms & tradeVisibility & control towerPricing, sales & finance

The client problem

GenAI pilots stall at the controls review: no grounding, no autonomy limits, no named owner for the exceptions — and documents, status messages and emails stay unstructured.

Outcomes

  • Supervised agent squads in production, with autonomy and guardrails set per agent
  • Trade documents, invoices and status messages read and checked consistently
  • People review only the exceptions, with the agent's draft and evidence in front of them

What we do

  • Agent design: roles, squads & autonomy levels
  • Document extraction for trade and carrier documents
  • ETA, delay and dwell-time prediction
  • Grounded assistants for sales and customer service
  • Evaluation & guardrails: policy, limits, kill switch

Typical engagements

  • AssessmentAgent opportunity and controls review
  • Pilot · 30-45 daysOne agent squad working real cases under your controls
  • BuildSquads integrated with your systems and scaled
  • Managed runAgentOps: monitoring, overrides, drift

Delivered with

Field Sales & Customer Visibility Run an agent live Governance & controls
03

Transform

Domain practices that change how a logistics business moves, stores, clears and sells, end to end, with our accelerators as the starting point.

Transform · Service line

Freight Forwarding, NVOCC & Trade Compliance

ForHead of freight / trade lanesHead of operationsCustoms & compliance
On the value chainForwarding & NVOCCPorts, CFS & ICDCustoms & tradeVisibility & control towerPricing, sales & finance

The client problem

Rates move weekly, consolidation and space are planned across many systems, containers wait at ports and CFSs, and every shipment carries documents that are keyed and checked by hand.

Outcomes

  • Yield, space and consolidation visible by trade lane and country
  • Live container, CFS and dwell views across facilities
  • Trade documents extracted and pre-checked before a broker files

What we do

  • Trade-lane yield & consolidation analytics
  • CFS, ICD & port visibility
  • Rate and surcharge monitoring
  • Trade-document extraction & pre-filing checks
  • HS-classification suggestions & denied-party screening

Typical engagements

  • AssessmentTrade-lane and operations data review
  • Pilot · 30-45 daysYield and CFS views for one region
  • BuildGlobal data lake and trade-lane data products
  • Managed runDashboard and pipeline operations under SLA

Delivered with

Trade-Lane Intelligence 360 Data Governance Hub Control Tower
Transform · Service line

Contract Logistics & Warehousing

ForHead of contract logisticsSite & warehouse headsKey accounts
On the value chainPorts, CFS & ICDWarehousing & 3PLExpress & last mileVisibility & control towerPricing, sales & finance

The client problem

Multi-client warehouses run to different SLAs, labour and space are planned site by site, inventory accuracy slips, and billing lags the activity actually performed.

Outcomes

  • SLA and margin visible by client, site and contract
  • Labour and slotting plans ready before peak
  • Activity-based billing reconciled before the invoice goes out

What we do

  • WMS & activity data integration
  • Labour planning & slotting optimisation
  • SLA-breach prediction
  • Inventory-accuracy & shrinkage analytics
  • Activity-based billing assurance

Typical engagements

  • AssessmentSite, SLA and billing diagnostic
  • Pilot · 30-45 daysOne site or one client end to end
  • BuildMulti-site data products and SLA control tower
  • Managed runSite-data and model operations under SLA

Delivered with

Revenue Assurance Control Tower RPA Automation
Transform · Service line

Road Freight, Express & Last-Mile

ForHead of road / fleetExpress & last-mile headsHub operations
On the value chainRoad & fleetWarehousing & 3PLExpress & last mileVisibility & control tower

The client problem

Trips are planned on the phone, empty return legs eat margin, first-attempt failures and returns decide the delivery P&L, and tolls, fuel and COD remittances are reconciled long after the event.

Outcomes

  • Load matching and back-haul plans that cut empty kilometres
  • Failed deliveries explained by reason and lane, with ETAs that hold
  • Trip costs and COD remittances reconciled per consignment

What we do

  • Trip, telematics & e-way bill integration
  • Load matching & back-haul planning
  • ETA and delivery-success prediction
  • NDR, return & fraud-risk classification
  • Trip-cost & COD reconciliation

Typical engagements

  • AssessmentNetwork, trip and delivery diagnostic
  • Pilot · 30-45 daysOne corridor or one city end to end
  • BuildNetwork data products and hub control tower
  • Managed runTelematics, scan and model operations under SLA

Delivered with

CLARION Control Tower RPA Automation
Transform · Service line

Commercial Excellence, Pricing & Visibility

ForHead of sales / key accountsCFOHead of customer experience
On the value chainForwarding & NVOCCRoad & fleetWarehousing & 3PLVisibility & control towerPricing, sales & finance

The client problem

Sales quote from spreadsheets, job and lane margin is known only after accruals reverse, carrier invoices go unchecked, and shippers learn about delays from an email.

Outcomes

  • Lane, customer and job margin in the sales team's hands
  • A self-service shipper platform with live status and proactive alerts
  • Carrier invoices audited against rates and milestones before payment

What we do

  • Field-sales app & next-best-action
  • Quote-to-booking & win/loss analytics
  • Customer visibility portal & control tower
  • Freight audit & carrier-invoice matching
  • Group, lane & job P&L with AI commentary

Typical engagements

  • AssessmentCommercial and customer-experience diagnostic
  • Pilot · 30-45 daysSales view or shipper portal for one region
  • BuildSales app, portal and margin data products
  • Managed runCommercial analytics and portal operations under SLA

Delivered with

Field Sales & Customer Visibility Group Executive Intelligence COMPASS NARRATOR
04

Run

Keep platforms, models and agents healthy and improving after go-live.

Run · Service line

Managed Services: DataOps, MLOps & AgentOps

ForCIOCOO
On the value chainForwarding & NVOCCRoad & fleetPorts, CFS & ICDExpress & last mileVisibility & control tower

The client problem

After go-live, carrier and port formats change, telematics feeds drop, peak season stresses every pipeline, and agents need someone watching overrides, limits and evaluation results around the clock.

Outcomes

  • Platforms, pipelines, models and agents run under agreed SLAs, peak season included
  • Continuous improvement driven by override and evaluation data
  • Your teams freed from L2/L3 support

What we do

  • Run & L2/L3 support
  • DataOps, including carrier, port, telematics and customs feeds
  • MLOps
  • AgentOps: logs, overrides, drift, kill switch
  • Continuous improvement

Typical engagements

  • AssessmentRun-readiness and support model review
  • Pilot · 30-45 daysHypercare for a newly live capability
  • BuildMonitoring, runbooks and SLAs
  • Managed runOngoing service under agreed SLAs

Delivered with

Governance & controls SCIKIQ Data Fabric
Our assets

What makes our services faster

Every engagement starts from SCIKIQ IP rather than a blank page. These assets are how we deliver — they come with the service.

1
SCIKIQ Data Fabric

The governed foundation every engagement runs on: the 4C method (Connect, Curate, Contextualize, Consume), 268 data sources, and governance, lineage, data quality, PII detection and masking, an AI/agent layer and security built in — cloud-agnostic on Azure, AWS or hybrid.

Explore the framework
2
Accelerators

Logistics accelerators — Trade-Lane Intelligence 360, Field Sales & Customer Visibility, Group Executive Intelligence and the Trading & Supply-Chain Cockpit — plus cross-industry accelerators such as CLARION, COMPASS and NARRATOR, tailored to your rules, data and controls.

Accelerators by service line
3
Supervised digital workforce

AI agents that plan, call tools and gather evidence on the governed data. Policy decides what goes straight through; people approve everything else; every step is logged and a kill switch halts all agents.

How it works Watch one work
How we engage

From a business outcome to measured value

Every engagement starts from the business outcome, not the technology. We frame it through the same business lens each time, then deliver in five phase-gated stages. Most logistics businesses start with a discovery and value case for one value-chain domain, then scale to the next on the same foundation.

How we frame an engagement

  1. 1Business outcome & KPI
  2. 2Value-chain domain
  3. 3Decisions
  4. 4Data
  5. 5AI & agents
  6. 6Governance & adoption
  7. 7Measured value

Delivery phases

Phase 1
Discover & value case

Outcome, domain and KPIs agreed; data and process assessment; baseline and business case.

Phase 2
Design

Decisions, data products, models, agents and controls designed for the chosen domain.

Phase 3
Build & integrate

Sprint delivery on the SCIKIQ Data Fabric, integrated with booking, TMS, WMS, terminal, customs and ERP systems; tested on real data.

Phase 4
Deploy & adopt

Go-live, people and process change, agent autonomy limits agreed with operations, customs, sales and finance; value tracked against the baseline.

Phase 5
Run & scale

Managed service — DataOps, MLOps and AgentOps under SLA — and the next domain on the same foundation.

Each phase ends with a gate signed off by your steering group; a pilot in one domain typically reaches a production-ready capability in 30-45 days. The SCIKIQ Data Fabric we build on

Engagement models

Staff Augmentation

Data engineers, architects, analysts and AI specialists embedded in your teams, under your delivery lead.

Project Delivery

Outcome-based delivery of an accelerator or platform build, owned end-to-end by SCIKIQ with phase gates.

Managed Services

We run and improve your data platforms, models and agents — DataOps, MLOps, AgentOps and support under agreed SLAs.

Weekly status Bi-weekly steering Phase-gated sign-off 30-45 day pilot → scale

Start with the outcome you need

Pick a domain and a KPI. We'll propose a discovery and value case or a 30-45 day pilot and show you what the first weeks look like.

Talk to us Take the self-assessment
Next chapter · 3 of 6
The foundation

Every domain above runs on the same governed data fabric — booking, TMS, WMS, terminal, customs and finance systems connected, curated, contextualised and consumed, with lineage from source to the board pack.

Next chapter: The foundation