Site Intelligence · Powered by Tekshot Vision AI

See exactly what is
really happening on site

Tekshot Vision AI captures what is happening on site as photos and video, analyses them to extract evidence, then sends that evidence straight into Output. The value is not in being able to view a photo — it is in the photo becoming the basis for acceptance and payment.

  • Captured on a basic phone
  • Results always come with a confidence level
  • The final verifier
The real site
Real evidence
  • Photos & video with GPS coordinates and timestamps
  • The AI suggests the work item and an estimated quantity
  • Engineering confirms it before it becomes evidence
  • Evidence feeds Output; it does not stop at a photo library

We do not claim the AI is always right

The people who evaluate the product inside a contractor are engineers. They trust a system that knows how to say it is unsure more than one that is always right. So every Vision result in ERPCons is shown confidence, and every case the machine is unsure about is routed to a human approver instead of being decided automatically.

  • No demos on a hand-picked photo set
  • We do not hide misrecognition cases
  • AI results are never used as a basis for payment without human approval

From the site to output

This is the whole journey of a single site photo. Step 4 — verifier — is mandatory and cannot be switched off.

1
CapturePhotos / video from a phone, a fixed camera or a drone
2
Attach contextGPS coordinates, timestamp, work item, position on the drawing
3
AI analysisSuggests the work item, progress and an estimated quantity — with its confidence level
4
VerifierEngineering approves, edits or rejects the AI suggestion — mandatory
5
Into OutputIt becomes official evidence for acceptance and payment
The output is what matters most

Stopping at step 3 leaves you with a smart photo library. The real value is in step 5: site evidence flowing into Quantity & quality acceptance, then continues on to Cost and Reconciliation.

The real interface (sample data)

erpcons.vn/app/site-reality/riverside Sample data
Project: Riverside Urban Area › Tower A › Level 5
Site analysis results — 26/04/2024
Photo captured
148
within 24 hours
AI highly confident (≥ 90%)
96
65% — fast-track approval
Needs a human approver
38
26% — low confidence
The AI cannot draw a conclusion
14
9% — manual handover
AI suggestions — every line shows its confidence
PhotoWork item suggested by the AILocationEstimated qtyConfidenceStatus
Slab concrete pourLevel 5 — grid A/1-3~ 42 m³ 94% Fast-track approval
Beam rebar fixingLevel 5 — grid B/2~ 3.1 tonnes 91% Fast-track approval
BlockworkLevel 4 — grid C~ 68 m² 72% Needs a human approver
Column formwork (2 options)Level 5 — grid D/4 58% Needs a human approver
Indeterminate — backlit photoLevel 5 — grid E The AI draws no conclusion
Nothing flows into Output automatically Every suggestion must be approved by engineering. The confidence level is used only to prioritise what to review first.

Interface shown with sample data. The 65% / 26% / 9% ratios are illustrative — not yet a measured benchmark. See §Limitations below.

Confidence & technical limits

This section is awaiting official figures from Product

Under the evidence principle (ERPCONS-WEB-UX-001 §10, item 10), the page must not publish AI capabilities without a benchmark. The content below is a frame to fill in, not measured figures. Do not publish this page before replacing them with real data.

Three levels of results

High confidence The AI is confident enough — the approver only has to confirm quickly
Needs confirmation The AI offers several options — a person decides which one is right
No conclusion The AI states clearly that it cannot process the case and hands over to manual capture

Conditions where the AI performs poorly

Published openly so users know up front, instead of discovering it after rollout.

  • Backlit shots, or night shots without enough light
  • The angle is too far away, or most of the work item is obstructed
  • The work item is mid-transition and not clearly defined yet
  • The material or construction method is not in the training set
  • [Awaiting Product to add the conditions actually recorded]

What Vision AI no do

  • Output is never recorded automatically without an approver
  • It does not replace acceptance against technical standards
  • It does not judge internal structural quality from a surface photo
  • It does not replace human supervision on site

Proven use cases

Awaiting Product sign-off on the list

We list only cases that ran on real projects with measurable results. The four cards below are a template — each card needs its scope, input data and measured result filled in.

Daily progress capture

Replace manual progress reports with time- and location-stamped photos.

To be filled in: which work item types it applies to · how many projects it has run on · measured results
Add evidence to the acceptance report

Photos attach automatically to the right work item and position on the drawing.

To be filled in: share of photos correctly tagged · time saved · data source
Detect safety breaches (HSE)

Detects missing PPE and hazardous areas without barriers.

To be filled in: which breach types it catches · measured accuracy · false alarm rate
Compare actual against plan at each milestone

Compare photos of the same spot across periods to see the progress gap.

To be filled in: required shooting conditions · acceptable margin of error

Runs on the devices actually used on site

The main users are site managers and field engineers on mid-range Android phones with unreliable mobile coverage. That is a design constraint, not a preference.

  • Capture and upload works on a mid-range Android phone
  • Works offline, syncs automatically once there is signal
  • Large touch targets that work with gloves on
  • Images are compressed on the device to save bandwidth
Trust Layer
A trusted platform for sustainable operations

Security — Transparency — Compliance — Ready to scale

SecurityMulti-layer data security
Data OwnershipData ownership
Audit TrailA complete audit trail
ComplianceLegal compliance
Integration & APIOpen, flexible connectivity
ImplementationImplementation & Training
Support & SLASupport & Commitment

Want to try it on your own site photos?

A Vision pilot runs on one project's real data with a clear scope and success criteria — a committed trial, not a demo.

  • An expert works alongside you
  • Scope and criteria agreed up front
  • Your data belongs to you