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AI Agent Developer: New York
Financial services firms in New York employ 3–5 analysts to generate daily market briefs. Each analyst pulls data from Bloomberg, compiles competitor filings from SEC EDGAR, and summarizes overnight news: 6–8 hours of work per brief. An AI agent wired to those same data sources generates the same brief in 20 minutes.
Legal firms face a parallel problem. Contract review routing currently requires a paralegal to read each incoming agreement, identify counterparty, extract unusual provisions, and route to the right reviewer. An agent handles the extraction and routing deterministically. The lawyer reviews the output, not the raw document.
We build these systems fixed-scope, with pricing shaped by the number of data source integrations and workflow complexity.
Describe the workflow you want to automate.
A senior analyst at an asset management firm earns $120,000–$180,000 per year. When 30–40% of that person's time goes to data gathering and document assembly, the math is straightforward: you are paying professional-grade salaries for clerical work.
The daily market brief at a hedge fund involves pulling overnight price moves, reading 8–12 regulatory filings from EDGAR, scanning five news sources, and producing a formatted summary by 7am. An agent connected to the Bloomberg Market Data API, SEC EDGAR full-text search, and a news aggregation feed produces the same document. The analyst reads it instead of writing it.
Contract review at law firms has the same structure. A paralegal reads the incoming agreement, identifies the counterparty, flags unusual indemnification or limitation-of-liability clauses, and routes the file to whichever attorney handles that client type. This takes 20–45 minutes per contract.
An agent with a document parser, a clause classifier, and a routing rules engine handles this in 90 seconds. The attorney receives a structured summary: counterparty identified, unusual provisions flagged, routing decision made. They review the summary and either confirm or override.
The agent handles information assembly. Your analysts handle judgment. Those are not the same skill, and they should not consume the same payroll.
The agent queries Bloomberg, EDGAR, and news APIs on schedule. No one needs to remember to pull the data or deal with API pagination.
A human reader identifies 80–90% of unusual clauses. The agent identifies 95%+ consistently, without fatigue, because it applies the same extraction logic every time.
Every routing decision the agent makes is logged with the reasoning that produced it. If a contract was routed incorrectly, you can trace exactly why.
The specific tool integrations and agent components common to financial services and legal workflows in this market.
Bloomberg Market Data API, SEC EDGAR full-text search, Refinitiv, and news aggregators. Structured output at each data fetch step so the agent never acts on malformed data.
PDF extraction, clause classification, entity recognition for counterparty and provision identification. Output is a typed schema, not free-form text.
Deterministic routing logic separate from the LLM. The agent proposes; the rules engine validates; the log records both. Humans override when needed.
Every agent run is logged: tool calls, outputs, latency, cost. We build a dashboard so your team can see exactly what the agent is doing and catch drift early.
Describe what your analysts or paralegals do today that you want an agent to handle. We'll reply within one business day with a rough scope and price range.