Turn a content or market question into an evidence-classified gap report — with every finding labelled by how well it is actually known.
Content Gap Finding Engine is an executable, evidence-led research engine for content and market research. It runs a defined research workflow and produces a report that distinguishes what has been verified from what has not.
It is not a content generator and not a keyword tool with a report bolted on. The engine owns the research logic, the orchestration, the scoring and the evidence trail — and it refuses to upgrade an unknown into a fact.
Most content research produces a confident-looking list built on unverifiable inputs. A tool reports a keyword volume, an inference is written as a fact, and a blocked source quietly becomes a plausible number. The output looks decision-ready but cannot be trusted.
Content Gap Finding Engine addresses this by making the evidence trail part of the product. Every finding carries its class, comparisons and scores are explicit, and where something could not be verified, the report says so instead of filling the gap.
It is not intended for bulk article generation or for anyone who wants a single number without the reasoning behind it.
The engine runs a nine-step research workflow, ending in a report.
The engine preserves a fixed set of evidence classes through the whole workflow, so a reader always knows how well something is actually known.
The engine never converts:
A source that is blocked or behind authentication is reported as blocked or auth-required — never replaced with a plausible-looking answer.
A runnable engine that owns the research logic, orchestration, adapters, scoring, evidence handling, storage, reports and execution.
A separate operator layer that owns detection, routing, instruction, fallback and the stand-in workflow. It never overwrites engine code.
When a full engine runtime is unavailable, the skill layer can run in a documented stand-in mode — and every artefact it produces is labelled as stand-in rather than presented as a full run.
Each prompt defines its input, context, engine action, expected output, assumptions and evidence handling.
A dedicated API credential setup guide, a built-in diagnostic command that reports pass or fail, and an automated test suite.
Sample input data so a first run needs no preparation, plus published checksums so a delivered package can be verified.
For a breakdown of how this documentation is organised, see Documentation.
Full package contents are summarised on Documentation.
The real engine evidence below demonstrates the genuine Content Gap Finding Engine package structure, analytical workflows, and evidence discipline. In live operation, CGFE ingests research inputs, computes multi-source intent discrepancies, classifies findings under strict evidence tags (with AUTH_REQUIRED and BLOCKED preserved where sources are gated), and compiles structured opportunity reports. Below is verified documentation and architectural evidence from the release repository.
Windows Explorer showing the Content Gap Finding Engine project structure, documentation, and configuration folders.
CGFE multi-source gap analysis mapping competitor topic coverage, intent discrepancies, and unaddressed search demand.
CGFE evidence tagging framework enforcing strict isolation between verified facts, direct quotes, benchmarks, and unverified signals.
Content Gap Finding Engine is the canonical public name for this product across the SOVEL platform, product registry, and customer packages, reflecting its architecture as an executable, evidence-led research engine.
The product is published and distributed under this name, with the permanent canonical URL /content-gap-finding-engine/.
Canonical public name verified
Comprehensive package documentation is included directly within the product archive. This product page serves as the public documentation and specification surface, with indexed platform guidance on Documentation.
Package documentation included
Version history and release notes are maintained directly in the product package changelog. The current release represents the active stable build (v1.0.0+), with lifetime 1.x maintenance updates included.
Active release
Customer support and technical inquiries are handled directly via support@sovel.pro. Review coverage guidelines, requirements, and triage workflows on Support & contact.
No. It is a research engine. It produces an evidence-classified gap and opportunity report with a strategy — not bulk articles.
The report records it as blocked or auth-required. The engine does not substitute a fabricated result.
It can record an estimate, but it will label it an estimate. An estimate is never presented as a fact.
Yes. Content Gap Finding Engine is available for direct purchase at ₹2,999 (INR) with instant digital delivery of the Python research engine, test suites, and diagnostic tooling.
Content Gap Finding Engine is built by P. Adhil Khan.
The product library shows each family, what it is for, and how the documented products actually work.
