Version your research like software and cut what it costs.

The fragmented survey toolchain quietly bills you in analyst hours, re-fielding, and per-seat fees. Siamang collapses the loop into one reproducible pipeline. Here's what that's worth.

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Attacks: {{ l.c }}

Estimate your annual savings.

Drag the inputs to match your team. Every figure is illustrative. Your real numbers go here.

Study-instances per year {{ instances }}
Each wave, pilot, or tracker counts as an instance.
Blended analyst rate {{ rateLabel }}/hr
Current tool spend replaced / yr {{ toolLabel }}
Survey builder + storage + BI you'd retire. Your number, not an assumed competitor price.
Savings assumption
Share of status-quo hours saved: 24% / 38% / 51% of 26.5 hrs per study-instance.
Net annual benefit
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PAYBACK{{ paybackLabel }}
ROI {{ roiLabel }} on this model's assumptions. Sanity-check it with your own numbers.
Analyst hours saved / yr{{ hoursLabel }}
Labor value recovered{{ laborLabel }}
Re-fielding cost avoided{{ errorLabel }}
Tool spend replaced{{ toolReplacedLabel }}
Siamang Pro / yr−$2,400
Beta pre-order: lock Pro at $1,200 for year one and payback drops to {{ paybackPreLabel }}.

Auditable model: 26.5 hrs per study-instance × % saved (24 / 38 / 51%) × rate; re-fielding avoided = instances × error-rate × $2,000 × reduction; benefit − Pro at $2,400/yr. Every input is illustrative. Replace with your own figures.

Harder to price. Just as real.

Reproducibility & audit
Every instrument change is a commit; every result re-runs; an audit log records who did what. Faster reviews, lower compliance and key-person risk.
No lock-in
The engine is source-available; your data exports to SPSS, CSV, Parquet and SQLite any time. Switching cost, and vendor leverage over you, drops to near zero.

Numbers are an argument. A pilot is proof.

Run one real study on the free 30-day Pro beta and measure the hours yourself. No credit card.