Tax Research Assistant combines document intelligence, profile-driven LLM workflows, and optional retrieval-augmented generation to help firms collect facts, analyze tax situations, and deliver more precise answers at scale.
Go beyond a generic chatbot with a system that collects the right facts, structures the right documents, and routes the right reasoning path for each taxpayer or business profile.
CPAs can specify the exact list of questions the assistant should ask to gather facts needed for a given return, planning scenario, or research issue.
The system uses the user’s profile, answers, and documents to decide which LLM calls, prompts, and reasoning paths to invoke.
Ingest a variety of tax and financial documents and convert them into normalized JSON for downstream reasoning and compliance workflows.
Handle broad and open-ended tax questions while preserving context from the user’s facts and supporting materials.
Use retrieval-augmented generation to ground answers in custom tax guidance, internal knowledge, or reference content when broader context is needed.
Support intake, tax research, and guided planning flows across individuals, entities, and specialized advisory use cases.
Tax Research Assistant creates a workflow layer between client inputs, tax documents, and LLM-powered analysis.
Start with CPA-defined questions, user profile data, and uploaded tax or financial documents to collect complete context.
Extract key tax-relevant data from source documents and normalize it into machine-usable JSON for downstream analysis.
Select the right LLM prompts, tools, and optional retrieval layer based on the user’s facts, entity type, and research need.
Instead of treating tax research like a one-shot prompt, the platform first builds context through guided intake, structured document extraction, and user-specific workflow routing.
The platform supports a guided tax workflow where the CPA decides what needs to be asked, and the system adapts the research process based on the answers.
Practitioners can create a question list tailored to a client scenario, planning issue, or compliance workflow.
The assistant can vary LLM calls and prompt strategy depending on the taxpayer profile and document context.
For broad questions, custom firm knowledge, or domain-specific interpretation, the platform can use a retrieval-augmented generation layer to ground answers in curated sources.
Bring in internal tax research notes, firm guidance, FAQs, or curated reference content to enrich the assistant’s answers.
When the user asks something wide-ranging or nuanced, retrieval helps supply richer and more targeted context than prompts alone.
Use the RAG layer only where it adds value, while keeping simpler profile-based workflows fast and lightweight.
Tax Research Assistant helps firms collect the right facts, extract structured data from documents, and generate more personalized tax guidance through profile-aware LLM workflows and optional retrieval grounding.