Numetiva

Legal disclosure / Imprint

Legal
Notice.

Business identification and responsible company contact.

Version: 24 October 2026

Company and contact disclosures for Numetiva, a product of K21SiliconSystemsPrivateLimited. This notice must be completed using the company’s official register details and reviewed for relevant market-specific information duties before publication.

01. Company identification

Legal entity: K21SiliconSystemsPrivateLimited
Registered office: Sunshine Hill County, Hyderabad, India
Corporate Identity Number (India): U62011TS2026PTC224636
Directors: Y. Suryanaraya Sharma & G. Subramanyam
Country of registration: India.

02. Contact

Business email: support@numetiva.com
Security reporting: security@numetiva.com
Privacy: privacy@numetiva.com

03. EU market disclosures

If business is directed to Germany or other EU markets, assess applicable provider-imprint requirements (including German DDG §5), VAT information, European establishment/representative details, online dispute information where required, and any applicable trade/professional registrations. Do not represent an Indian company as a German UG or GmbH until that entity actually exists.

04. Legal framework

For website use see our Terms and Conditions; for enquiries see our Privacy Policy. Technical figures and internal quality evidence are explained in Product Validation.

Numetiva / vector chart
100%Open SVG ↗

Zoom for individual dies and labels. Drag or scroll to pan. + / - to zoom; 0 to fit.

Numetiva / interactive product tour

From a question to a checked output

Your question.
A reviewable script.

Use the assistant to draft Python, inspect the code in the workbench, then run it against your worksheet. Bring the latest error into Review / fix when the script needs attention.

  1. 01
    Ask with context.

    Name the response, predictors and the chart you need.

  2. 02
    Inspect the draft.

    Check the column names, transformations and method.

  3. 03
    Run and review.

    Use the returned output and errors to guide the next step.

Explore AI & Python
Python / exampleWorksheet context
import numpy as np
import matplotlib.pyplot as plt

x = df["Tool_Wear_um"].to_numpy()
y = df["Vibration_RMS_g"].to_numpy()
valid = np.isfinite(x) & np.isfinite(y)
x, y = x[valid], y[valid]

fig, ax = plt.subplots()
ax.scatter(x, y, s=18, alpha=0.7)
coefficients = np.polyfit(x, y, 2)
grid = np.linspace(x.min(), x.max(), 200)
ax.plot(grid, np.polyval(coefficients, grid))
ax.set(xlabel="Tool wear / µm",
       ylabel="Vibration / g")
plt.show()
About this product tour