What is agentic chat?
Agentic chat is a conversation where the chat box fronts an orchestration rather than a single model: a system that decomposes your request, routes sub-tasks to specialized agents and tools, pulls live data, verifies and cites what comes back, and, where you allow it, executes the result. The interface looks like any chat. The difference is everything behind it.
The distinction matters because the failure modes differ. A plain chatbot fails by hallucinating: it answers from parametric memory, confidently. An agentic chat fails loudly or not at all: tools return real data or errors, citations are checkable, and actions pass through gates. For domains where being wrong costs money, the second architecture is the only acceptable one.
The four-layer test of a real agentic chat
- Orchestration: does one question fan out to multiple specialized agents and tools, or does one model just write paragraphs? Ask something compound ("compare my exposure to rate cuts against what hedge funds did last quarter") and watch whether the system visibly works.
- Proprietary data: do the tools reach data the base model cannot know: live positions, filings as they land, private-market records, real-time tape?
- Citations: can you click through to the filing, the print, the disclosure behind every claim?
- Execution: can the conversation end in an action, within guardrails you set?
General assistants pass none of these for finance. Most finance chatbots pass one. The bar for "most advanced" is passing all four, with depth.
See it on your own portfolio: connect a broker and ask Tengu anything about your money.
Try Tengu freeTengu Chat: the most advanced agentic chat in finance
The claim is specific and checkable. Tengu Chat runs proprietary multi-agent orchestration over 229 finance tools, the same surface exposed by the Tengu API: SEC filings and full-text search, options flow, insider and congressional activity (official STOCK Act disclosures), fundamentals, macro series, real-time prices across 28+ venues, and a private-markets graph covering 10.5M private companies, their funding rounds, investors, and the relationships between them. No general assistant and no broker chatbot carries that data surface.
It is grounded in your live portfolio across 25+ brokerages: every conversation loads your actual positions, so "should I trim this?" is answered about your lot sizes, your cost basis, your concentration. Every claim ships with citations. And it is the only chat in the category whose conversation can end in execution: the trades you approve route through your own broker, in the accounts you already hold, behind position limits, leverage caps, and drawdown circuit breakers. Tengu trades its own capital live on the same engine. Same brain, by voice too: Tengu Voice is the identical orchestration, spoken.
Agentic chat vs ChatGPT, Claude, and Perplexity for finance
| ChatGPT / Claude / Perplexity | Broker chatbots | Tengu Chat | |
|---|---|---|---|
| Architecture | General model + web search | Scripted + single model | Proprietary multi-agent orchestration |
| Finance data surface | Public web | That broker's data | 229 tools: filings, flow, insiders, congress, macro, 10.5M private companies |
| Knows your portfolio | No | One account | Yes, 25+ brokerages, live |
| Citations to primary sources | Web links (Perplexity cites well), rarely filings | Rare | Every claim |
| Can execute | No | Sometimes, in-app | Yes: your approval, your broker, risk-gated |
| Voice with the same brain | Voice, no portfolio | No | Yes (Tengu Voice) |
| Price | $20/mo | Free with account | $20/mo |
The price row is the point: Tengu Chat sits at the same $20 shelf as ChatGPT Plus and Claude Pro. The difference is that it knows your money, and it can act.
Why generalist chats cannot catch up by adding plugins
The gap is structural, not a feature backlog. First, data rights: the surface Tengu orchestrates includes licensed and assembled datasets a general assistant cannot legally crawl. Second, account plumbing: read-and-trade permissions across 25+ brokerages took the better part of the product's life to build and certify; a plugin cannot shortcut custody-grade integrations. Third, accountability: execution requires risk gates, audit trails, and a vendor willing to run its own money through the same pipes. That is why the practical architecture is the inverse: generalist agents plug into Tengu (the API is Anthropic-compatible and MCP-native), gaining the finance surface instead of rebuilding it.