Stocks Assistant
Most investment tools provide users with additional data, but Stocks Assistant offers them more. understanding. The product is built around a core insight: financial markets produce two distinct streams of signal that rarely get analyzed together what companies say (earnings calls, management guidance) and what the market bets (options positioning, call/put interest).
The assistant converts complete earnings call transcripts into organized insights, generating a standardized output. Momentum Score (0–100) across four quarters and a Company Performance Score It translates short-term noise into long-lasting signals. When it comes to the market, it deciphers options chains to reveal clear positioning intentions such as 'Bullish: more interest in calls than puts.'
Why accuracy matters here: By combining transcript intelligence with options data normalized into consistent scoring models, the assistant eliminates the most common investor error reacting to a single data point in isolation.
Stocks Portfolio AI Agent
Stocks Assistant delivers the intelligence layer. Stocks Portfolio AI Agent takes the next step turning that intelligence into concrete, personalized portfolio recommendations tied to each investor's actual holdings, goals, and account structure.
The agent begins by understanding the investor: holdings, account types (taxable vs. Roth), target allocations, concentration limits, and time horizon. It then layers in company-level signals to evaluate each position in context suggesting rebalancing moves, entry and exit timing, and stop-loss logic.
One of its most differentiated capabilities is tax-aware optimization: it identifies unrealized losses for harvesting, helps offset gains, and reasons across account types to improve after-tax outcomes work that has historically required a financial advisor and a CPA working together.
Why accuracy matters here: Portfolio recommendations without context are noise. By anchoring every suggestion to the user's specific goals and holdings and grounding signal in the same rigorous scoring models from Stocks Assistant the agent ensures relevance, not just directional correctness.
Financial Planner AI Assistant
Financial Planner AI Assistant aims to disrupt the conventional pattern of annual interactions with financial planners by offering a straightforward solution. Financial planning should adapt as life changes, rather than being forgotten after a yearly check-in.
The assistant monitors retirement readiness, tracks cash flow, balances savings goals against debt and insurance obligations, and surfaces the next financial action whenever it matters. For financial institutions and fintech platforms, it delivers personalized planning experiences at scale without requiring a dedicated advisor per user.
Why accuracy matters here: Life financial decisions compound over decades. An assistant that gives gently wrong guidance can meaningfully damage a family's financial outcomes. DataKnobs designed this product to continuously reassess based on real inputs not static snapshots.
E-commerce Analysis Agent
The dysfunction in financial analysis within e-commerce is characterized by an abundance of dashboards but a lack of comprehension regarding the reasons behind metric fluctuations and how to address them. The E-commerce Analysis Agent has been developed to address this issue. always-on business analyst explaining causes, not just reporting numbers.
The agent processes various data points including traffic, product views, cart activity, checkout data, purchases, and post-purchase signals to analyze the entire customer journey. It pinpoints areas of improvement and growth opportunities, and provides financial recommendations such as pricing adjustments, bundling options, funnel enhancements, and lifecycle changes based on revenue impact and customer value.
Why accuracy matters here: E-commerce teams frequently optimize a leaky funnel metric without understanding downstream revenue impact. This agent connects behavior data to financial outcomes ensuring recommendations are grounded in margin implications and customer LTV, not just click rates.
Tax Research Assistant
Tax research is one of the most challenging tasks for AI to achieve accuracy. The consequences are significant: an incorrect response leads to financial losses, compliance issues, or advice that a licensed professional cannot support. DataKnobs developed the Tax Research Assistant with this critical consideration in mind. design center not an afterthought.
Instead of a basic tax chatbot, the product is a well-organized workflow system. CPAs set up specific intake questions for different client situations. The assistant gathers all necessary information, standardizes W-2s, 1099s, and K-1s into JSON format, and guides each question through a personalized logic path. An optional RAG layer bases responses on the company's internal tax guidance and reference materials.
Why accuracy matters here: Ensuring accuracy in tax responses is crucial, which is why DataKnobs has developed a system that collects structured facts and routes reasoning through a profile-specific workflow to avoid the dangers of generic LLM responses. architected not hoped for.
The DataKnobs Engineering Philosophy
Structured Before Generative
Prior to reaching the generative AI layer, data is organized and standardized. Earnings transcripts are transformed into scoring models, while tax documents are converted into JSON format. This process is crucial for ensuring accuracy.
Context Before Response
Whether it's a CPA's intake questionnaire or an investor's portfolio profile, every agent grounds its recommendations in the specific context of the person asking never generic best practices.
Signal, Not Noise
Scoring models, funnel analysis, and workflow routing all aim to condense intricate, noisy data into understandable signals that enhance decision-making by creating a compressed product.
Action, Not Just Insight
Every product closes the loop from analysis to recommendation. Users aren't left to translate a dashboard into a decision the agent does that translation explicitly.
Ready to deploy finance AI that demands accuracy?
Discover the complete range of finance AI tools from DataKnobs or schedule a demo to witness them in action.