AI Research Assistant for capital markets

Scale research coverage without growing headcount

The AI Research Assistant redefines research economics by enabling your analysts to cover more ground, more quickly, without adding resources. It eliminates manual data prep and disconnected workflows, delivering instant, contextual answers from both structured and unstructured sources. These answers are accurate, cited, and grounded in verifiable data.

The result is richer insights, faster decisions, and significantly expanded coverage capacity at a lower cost. Below are just some of the improvements AI Research Assistant brings to help accelerate your analysts:

analyst stock coverage

100%

query response accuracy

10+

petabytes processed

Key capabilities

The AI Research Assistant combines powerful analytics with intuitive natural language interfaces to streamline every stage of the research process. From accessing real-time and historical data to generating accurate insights and summaries, it helps teams move faster, work smarter, and deliver consistent, client-ready output at scale.

Context-aware understanding

Applies a temporal lens to research by automatically narrowing analysis to relevant time windows and tracking how events evolve for richer insight.

On-demand time-series analytics

Dynamically computes new insights such as volatility, moving averages, or peer comparisons using our high-performance time-series engine.

Cross-domain intelligence

Connects and analyzes SEC filings, transaction data, proprietary research, and real-time market feeds within a single query.

Agentic workflow automation

Agents orchestrate ingestion, analysis, and publishing tasks, allowing teams to instantly generate outputs for client reports.

Overcome these challenges

Research workflows are increasingly strained by data complexity, fragmented systems, and the need for faster insight. Analysts spend more time preparing than analyzing, making it harder to scale coverage, respond to market events, or deliver consistently high-value recommendations. AI Research Assistant helps you overcome these challenges:

Too much manual work

Analysts waste hours chasing filings, forecasts, and market data. Copying between systems slows output and leaves less time for strategic thinking, client engagement, and high-value insight.

Fragmented data stack

Structured and unstructured data, like earnings forecasts, filings, and market data, sit in disconnected systems. Without unified access, analysts struggle to generate fast, complete market views.

Unscalable coverage model

Scaling research means hiring more analysts or lowering quality. As demands increase, this trade-off limits coverage, slows delivery, and makes it hard to meet client expectations.

Insights lack traceability

Without clear citations or context, insights are hard to trust or validate. Analysts need transparent, source-backed answers to support compliance and ensure decision-making confidence.

Benefits

Faster insight generation

Delivers complete research summaries, including supporting data and visuals, in seconds.

Advanced analytical reasoning

Executes multi-step calculations on structured data in real time, enabling precise, on-demand answers to complex market and financial questions.

Greater analyst productivity

Automates repetitive workflows so analysts can focus on interpreting findings and deliver differentiated insights for more clients.

Trusted, verifiable answers

Ground all outputs in real data with source citations and audit trails, minimizing hallucinations and enabling compliance confidence.

How it works

It’s built on a chain-of-thought, agent-powered RAG architecture that enables natural language querying across structured and unstructured data. This includes SEC filings, analyst reports, internal documents, and market data, to compute, contextualize, and publish responses automatically.

This powerful system transforms how analysts work by eliminating the friction between questions and answers. Instead of spending hours navigating systems and piecing together information manually, they can ask natural language questions and get back clear, actionable, and source-backed insights in seconds.

Ask questions, get answers

Use natural language to query structured, unstructured, and time series data in one step. No code, no data prep, and no switching between systems.

Intelligent automation at real-time speed

AI agents retrieve data, analyze context, and deliver insights instantly using our in-memory analytics engine optimized for live market data.

Traceable and trusted outputs

Every answer includes citations and context, so analysts can validate insights, meet compliance requirements, and share results with confidence.

Why KX?

Time-series DNA

We were purpose-built for capital markets, with native support for high-volume, high-frequency, and time-aware data. From intraday volatility to long-horizon trends, we help teams extract insight across any timeframe.

Enterprise-grade scale

While other platforms falter at scale, we handle billions of rows in real time with sub-millisecond performance, meeting the latency, throughput, and compliance demands of the most data-intensive trading environments.

Faster path to value

We enable faster AI innovation in capital markets with validated high value use cases, NVIDIA-accelerated infrastructure, and tested frameworks that streamline deployment.

Demo the world’s fastest database for vector, time-series, and real-time analytics

Start your journey to becoming an AI-first enterprise with 100x* more performant data and MLOps pipelines.

Process data at unmatched speed and scale

Build high-performance data-driven applications

Turbocharge analytics tools in the cloud, on premise, or at the edge

*Based on time-series queries running in real-world use cases on customer environments.

AI Research Assistant: Expand coverage and accelerate insights

Scale research coverage without growing headcount