Conservation Technology Services

Make your patrol data
actually reportable.

Protected areas running SMART or M-STrIPES already capture the field data. We build the analytics over it — and the animal, veterinary, staff and reporting systems those tools were never designed to cover.

The market, and our delivery
~100
Countries using SMART *
1,500+
Ecosystems using SMART *
437ha
Park we delivered for
4-6mo
Our delivery timeline

* SMART Partnership figures describing the installed base, not Andolasoft reach. The lower two describe our Nandankanan delivery.

We do not replace SMART or M-STrIPES

SMART is open-source, free, and the established standard for ranger-based patrol monitoring — used across roughly 100 countries. In India, tiger reserves largely run M-STrIPES, the National Tiger Conservation Authority’s own system. Neither is a problem to be solved. The gap is what sits around them.

What SMART and M-STrIPES already do

Leave these where they are.

  • Ranger-based patrol data capture in the field
  • Spatial recording of patrol routes and coverage
  • Logging of threats, illegal activity and wildlife observations
  • The established conservation data model and sector practice

What we build around them

The layer these tools were never meant to be.

  • Analytics and dashboards over patrol and observation data
  • Animal inventory, veterinary and out-patient records
  • Staff rosters, beat allocation and duty attendance
  • Incident workflows and departmental reporting
  • Custom field applications where a standard tool does not fit
  • Integration between systems that currently do not talk

We build the surrounding systems and the analytics layer. We are not a SMART Partnership member and do not distribute or fork SMART.

Where we sit relative to your patrol tool

Your patrol tool keeps doing what it does. We read from it into a separate reporting database, define the metrics once, and serve dashboards from there.

Analytics architecture alongside SMART or M-STrIPESSMART or M-STrIPES continues to capture ranger patrol data and is left unchanged. Data is read out of it — by export, database replica or API depending on the deployment — into a separate read-only reporting database, alongside other departmental systems. A semantic layer defines patrol effort, encounter rate, coverage and gaps once. Apache Superset serves dashboards from that layer to officers, scoped by role and aggregated for wider audiences.YOUR SYSTEMSSMART / M-STrIPESRanger patrol captureUnchanged. We do not fork,replace or write to it.Other departmentalsystems and registersOUR LAYERReporting databaseRead-only replica · PostgreSQL + PostGISexport · replica · APISemantic layerEffort · encounter rate · coverage · gapsMetrics defined once, soevery dashboard agrees.Apache SupersetDashboards and reportsOpen source — no per-seatcost for viewers.Officers and departmentRole-scoped access;aggregated for wider audiences.

The extraction step is deliberately unspecified: a supported export, a database replica or a scheduled job against an API, depending on how your tool is deployed. What matters architecturally is the separation — analytical queries never hit the database your rangers sync against.

Services around your patrol tool

Six ways we add to a protected area or conservation department already running SMART, M-STrIPES, or its own field system.

Patrol analytics dashboards

Your patrol tool records the data; it is not a BI platform. We build dashboards over it on Apache Superset — coverage, effort, threat distribution and trend over time, in one place for managers.

Data integration

Bridging patrol data to the other systems a protected area or department runs, so reporting draws on one picture rather than several disconnected exports.

Complementary systems

Animal inventory, veterinary and out-patient records, staff rosters and incident workflows — the operational functions a patrol tool is not designed to hold.

Custom field applications

Where the standard tool does not fit a local workflow, purpose-built mobile capture for field staff — as delivered for Nandankanan Zoological Park.

Departmental and statutory reporting

Turning operational data into the periodic returns a forest department or conservation authority actually has to file.

Ongoing support

Managed support for the analytics and integration layer we build, in the same model we run for Apache Superset deployments.

What patrol analytics actually look like

Effort, coverage and findings in one place — normalised by patrol effort, so two periods, two ranges or two teams can be compared honestly.

Representative layout with illustrative data — not client data
Patrol analytics overview
Patrol effort
3,412 km
this quarter
Grid coverage
78%
cells visited, 30 days
Encounter rate
0.42
findings per patrol-km
Coverage gaps
14
cells unvisited 30d+
Patrol effort by range
Range 191
Range 276
Range 368
Range 452
Range 537
Range 624
Effort-normalised finding rate
Rolling 12 periods
Findings by category
Snare / trap found 31%Illegal entry 27%Wildlife sighting 24%Habitat disturbance 18%

Real dashboards are not published. Patrol coverage, patrol gaps and species locations are directly useful to poachers, so access in a deployed system is scoped by role and aggregated for wider audiences.

Comparable Delivery

Nandankanan Zoological Park

Odisha Forest Department, Bhubaneswar, India

We have not published a SMART integration. Our directly comparable delivery is Nandankanan — a 437-hectare park and the first Indian zoo admitted to WAZA — where we built daily patrol logging, incident reporting, animal inventory, veterinary management and integrated analytics dashboards.

Read the full case study

Scope delivered

  • Daily patrol logging (mobile)
  • Incident reporting and escalation
  • Animal inventory management
  • Veterinary and out-patient records
  • Analytics dashboard integration
  • Departmental and statutory reporting
CMMI Level 3 appraisedDelivered for a state forest departmentApache Superset practice

Common questions

Do you replace SMART or M-STrIPES?
No. SMART is open-source, free, and the established standard for ranger-based patrol monitoring across roughly 100 countries; M-STrIPES is the National Tiger Conservation Authority system used across Indian tiger reserves. We do not compete with either. We build the analytics layer over their data, and the operational systems they were never designed to cover.
Why would we need analytics if SMART already reports?
Patrol tools report on patrols. A protected area or department usually needs a wider view — patrol effort alongside incidents, staffing, veterinary activity and budget — and needs it in a form that goes to officers and boards. That consolidation is a business intelligence problem, which is the practice we run on Apache Superset.
Have you delivered a SMART integration before?
Our directly comparable delivery is Nandankanan Zoological Park, where we built daily patrol logging, incident reporting, animal inventory, veterinary management and integrated analytics dashboards. That is patrol and field systems work, and our Apache Superset practice is the analytics layer. We are not a SMART Partnership member and we do not distribute or fork SMART.
Why Apache Superset rather than a commercial BI tool?
Superset is open-source with no per-seat licensing, which matters for conservation bodies and government departments where adding viewers should not add cost. It also keeps data residency under your control. We deliver Superset consulting, dashboards, plugin development and managed support as a dedicated practice.
Do you work with government conservation bodies?
Yes. Nandankanan Zoological Park is operated by the Odisha Forest Department, and that engagement included a scheme analysis and policy planning toolkit covering scheme design, development and monitoring.

Request a Patrol Reporting Audit

A review of what your patrol tool captures today against what your officers actually need to see — and a written finding on the dashboards and integrations worth building. Yours to act on either way.

We do not replace your patrol tool. We build what sits around it.