Neighborhood Intelligence, Inc.: total liabilities

What this measure means

Recognized obligations at the reporting date. The definition and scope differ from interest-bearing debt.

Exact concept: us-gaap:Liabilities. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2010-12-31 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• Neighborhood Intelligence, Inc.: total assets
• Neighborhood Intelligence, Inc.: stockholders equity
• Neighborhood Intelligence, Inc.: cash and cash equivalents
• Neighborhood Intelligence, Inc.: net income or loss
• Neighborhood Intelligence, Inc.: operating cash flow
• Neighborhood Intelligence, Inc.: capital expenditure payments
• Neighborhood Intelligence, Inc.: contract revenue excluding tax
• Neighborhood Intelligence, Inc.: financing cash flow
• Neighborhood Intelligence, Inc.: investing cash flow
• Neighborhood Intelligence, Inc.: retained earnings or deficit
• Neighborhood Intelligence, Inc.: basic weighted-average shares
• Neighborhood Intelligence, Inc.: diluted weighted-average shares
• Neighborhood Intelligence, Inc.: basic earnings per share
• Neighborhood Intelligence, Inc.: diluted earnings per share
• Neighborhood Intelligence, Inc.: income tax expense or benefit
• Neighborhood Intelligence, Inc.: net property, plant and equipment
• Neighborhood Intelligence, Inc.: share-based compensation expense
• Neighborhood Intelligence, Inc.: operating income or loss
• Neighborhood Intelligence, Inc.: current assets
• Neighborhood Intelligence, Inc.: interest expense
• Neighborhood Intelligence, Inc.: current liabilities
• Neighborhood Intelligence, Inc.: current accounts payable
• Neighborhood Intelligence, Inc.: goodwill carrying amount
• Neighborhood Intelligence, Inc.: net finite-lived intangible assets
• Neighborhood Intelligence, Inc.: net current accounts receivable
• Neighborhood Intelligence, Inc.: common-stock repurchase payments
• Neighborhood Intelligence, Inc.: operating expenses
• Neighborhood Intelligence, Inc.: net inventory
• Neighborhood Intelligence, Inc.: gross profit

Inspect the source

Entity

Neighborhood Intelligence, Inc. / CIK 0001130713

Captured

2026-09-20T07:40:59.289Z

SEC response SHA-256

b0eef461d321d3660641c788012dadae21f288e59d477e2c40d7051cb4c25bbb

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

• Get an API key and run your first validation
• Connect the MCP server to your coding assistant
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001130713.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))