AI Portfolio Intelligence
We built an AI portfolio intelligence platform. Investment managers query multi-source financial data and historical asset performance in natural language. Answers cite structured financial-tool output.
GenPF needed to orchestrate AI models by task. Its RAG system had to retrieve documents and structured financial-tool output. Historical data needed low-latency processing, normalized provider data, and caching that balanced speed with freshness.
AI Portfolio Intelligence
A modular RAG architecture uses LangGraph for multi-step reasoning. Tool-aware prompts let models select and execute financial tools. The platform combines market, macroeconomic, and news data. Pre-computation handles heavy analytics, while streaming returns results to the frontend.
LangGraph provided mature, structured agent workflows. Pre-computation reduced latency for historical analytics. Tool-driven RAG lets LLMs call domain tools. We accepted controlled staleness for performance and extra orchestration overhead for broader model capability.
Multi-layer caching covers analytics and API responses. RAG combines unstructured explanations with structured financial output. Pre-computed datasets speed critical queries. Streaming keeps long computations responsive. A tool layer connects LLMs to financial APIs and internal analytics.
Built a working system for historical asset analysis and financial-tool selection.
Generated explainable answers through multi-tool RAG.
Pre-computation made heavy analytics usable.
Tool-augmented RAG beyond document retrieval.
Multiple financial providers unified into one analytical layer.
Pre-computation for high-latency workloads.
LLMs that reason over structured tools and text.
Financial AI needs data pipelines and model reasoning designed together. Prompt engineering alone is insufficient.
Applicable to investment platforms needing explainable AI and historical analytics. It also fits fintech products combining real-time data with tool-augmented RAG.
We specialize in ai integration and mvp for fintech companies. If you're facing challenges like the ones we solved for GenPF, let's talk.
