Automate market and macro research with AI agentsthat cite every source.

No. Every report stops at a HITL gate so the analyst signs off on the regime call, the cited papers, and the feature proposals before anything goes to PMs or risk. Lift the gate per template once the workflow has earned the trust.

Three ways. Static context attaches your house view, coverage list, and risk limits to specific personas on every run. The rag_retrieve tool lets MarketAnalyst and LiteratureSpecialist pull from filings, transcripts, and prior notes on demand. Cross-run memory carries last week's thesis into this week's update so follow ups do not start from zero.

It sits next to them. AlphaSense and Sentieo are search and excerpt surfaces over filings and transcripts. Melaya is the reasoning layer that runs MarketAnalyst, MacroEconomist, and LiteratureSpecialist on a schedule and writes the brief, with your sources cited inline.

Hebbia and BamSEC focus on document Q and A over SEC filings. Melaya plugs SEC EDGAR in as a scoped tool that any persona can call, then composes a multi step workflow around it with the 3 layer knowledge model so the same answer is reproducible next quarter.

Drafts cite specific paragraphs from filings, FRED series IDs, and arXiv identifiers. The LiteratureSpecialist is required to surface one contradicting paper per thesis, so the tone reads as a working analyst note instead of a confident summary.

Any. Claude on LiteratureSpecialist where long context and reasoning quality matter, GPT on DataScientist for code drafting, a local Ollama on MarketAnalyst when the on chain dataset cannot leave your network. Each persona picks its own.

With FRED, SEC EDGAR, and arXiv tools enabled, the macro briefing workflow is a 4 node canvas: pull series, summarize, cite, approve. Most teams ship it in a working session and have the first reviewed brief in their inbox the same day.

Every run logs every tool call, every retrieved chunk, every model invocation, and every approval. Replay any run to see which FRED series, which 10 K paragraph, and which arXiv paper drove the conclusion. The audit log is the methodology log.

n8n, Zapier, and Make execute predefined trigger-action steps, and they win on connector breadth for simple linear automations. They cannot plan a deep dive: Melaya's Market Analyst, Macro Economist, Literature Specialist, and Data Scientist reason across steps, scoped by read only bundles like sec_edgar_tools and fred_tools, with human-in-the-loop approval on every write.

Write the script if a scheduled chart pull is all you need. A script cannot make the Market Analyst's regime call or surface the contradicting paper the Literature Specialist always finds. Melaya adds per-step model routing across 23 providers, full run traces, and deterministic-first evaluation, so every brief is reproducible and auditable.

Yes. Save any Melaya run as a template and rerun the same four persona crew on a new ticker with the inputs swapped. The knowledge bundle builds a per workflow vector store from prior notes and won thesis memos, so the crew retrieves last quarter's work instead of researching the name from scratch.

Yes. Melaya runs in the cloud or on your local runner, and per-step model routing lets you pin steps that touch house coverage to a local model. Indexing new corpora into the knowledge bundle's vector store is HITL gated, while public pulls through arxiv_tools and yahoo_finance_tools can stay in the cloud.

Melaya runs deterministic-first evaluation: rule-based checks fire before any model-graded review. The checks verify each claim carries a FRED series id from fred_tools, an EDGAR reference from sec_edgar_tools, or an arXiv id from arxiv_tools, and a brief that fails never reaches the analyst sign off gate. Full run traces show which source backs each step.