About DOCSI.AI
Evidence-first AI research for decisions that need to stand up to scrutiny.
DOCSI.AI is governed, scrutiny-facing research software — a Command Line Tool for advanced AI research, currently in private beta — that turns complex questions into reviewable plans, traceable evidence, and polished reports across the web, news, scientific papers, and patent data, with explicit control over scope, cost, and time.
Plan the research. Control the spend. Trace every citation.
Instead of an opaque block of generated text, DOCSI.AI creates an inspectable research workspace: the research plan, retrieved sources, structured findings, cost ledger, quality artifacts, and the final cited report. The result can be reviewed, challenged, resumed, and extended without starting over.
The problem
Professional research needs more than an answer
DOCSI.AI treats research as a governed process rather than a single prompt. You review and approve the strategy before execution, the engine records what it used, and the report is built from the evidence collected during that run.
How it works
One controlled workflow from question to report
Clarify the objective
Adaptive questions turn an ambiguous request into a focused research brief — without a long questionnaire when the goal is already clear.
Build and approve the plan
A structured research tree with goals, searches, known URLs, evidence needs, and report sections. Review the source mix and cost range, then approve, edit, or replan.
Search the right sources
Each research need is routed to the right source type — general web, current news, Scholar, Patents, direct documents, or clearly labeled model knowledge.
Retrieve and structure evidence
Sources are ranked, deduplicated, and fetched through a resilient retrieval ladder, becoming stored artifacts and focused, source-linked learnings.
Investigate recursively
New findings spawn targeted follow-up questions and searches — continuing while it adds value and stays inside depth, source, budget, and time limits.
Synthesize and deliver
A cited report with citations closed against the stored source set, surfaced coverage gaps, report QA, and export to Markdown, HTML, or a designed PDF.
Source-aware planning
Search the right source for each question
Current facts, organizations, products, markets, regulation, standards, and events.
Scientific evidence, literature reviews, methods, benchmarks, and foundational work.
Prior-art discovery, disclosed mechanisms, inventors, assignees, and filing chronology.
Known primary sources, reports, standards, papers, and canonical patent documents.
Background or definitional context, stored and labeled separately from fetched evidence.
Source-aware planning matters. Scholar citation counts stay context, not a quality score. Patent documents establish what was disclosed — not whether a technology works commercially, or whether a patent is valid, enforceable, or safe to operate around. Those questions require complementary evidence and, where appropriate, qualified professional advice.
Trust
Evidence traceability by design
Persisted sources
Retrieved pages and documents become run-specific artifacts, not disposable browsing context.
Closed-world citations
Reports may cite only source identifiers created during the run; fabricated ones are removed.
Quote-aware extraction
Supporting excerpts and verification flags are retained where deterministic checking is possible.
Document-level dedup
Academic versions and repeated discovery paths don't become fake corroborating sources.
Visited web evidence
Every URL in the final References belongs to a source artifact actually retrieved.
Honest gaps
Single-source support, contradictions, and missing coverage stay visible instead of smoothed over.
Honest scope: closed-world citations eliminate fabricated references, not misreading of a source's actual meaning. Quote verification is best-effort. DOCSI.AI creates a stronger evidence trail for evaluating how a conclusion was reached — it does not promise perfect accuracy or replace expert review.
Control the economics of every run
Research quality and research spend are planned together. Before execution you see the proposed work, its source mix, a low/expected/high estimate, and which budget dimension is most likely to bind. The engine then enforces:
- A total USD budget and provider-specific limits
- Source and node ceilings plus a wall-clock limit
- Preflight checks before billable operations
- A protected synthesis reserve for the best possible report
- An append-only spend ledger for every committed operation
Professional deliverables, not raw output
- Structured Markdown reports with generated Contents and References
- Browser-ready HTML
- Designed, branded PDF with professional typography and page structure
- Evidence-backed charts whose values resolve to accepted source material
- Optional, explicitly budgeted presentation illustrations
- Audit artifacts for citations, evidence, charts, images, and export status
Where it fits
Where DOCSI.AI creates value
DOCSI.AI supports research and discovery; it does not replace legal opinions, scientific validation, regulated professional judgment, or the decision-maker accountable for the final conclusion.
Availability
Current delivery model
DOCSI.AI is available today as a Command Line Tool built for advanced AI research. It runs locally, supports both interactive and headless operation, and stores every project in an inspectable workspace.
Research that can be reviewed, continued, and trusted — not just generated.
Plan the research. Control the spend. Trace every citation.