SimianX AI User Interview (Dialogue): Deloitte Audit Manager
In this dialogue-style interview, we speak with the manager, an audit Manager at Deloitte, who actively trades—primarily day trading with occasional swing positions. He explains how SimianX AI fits into his workflow, why multi-agent analysis beats manual toggling across sites, and what real-time features he hopes to see next.
Background & Motivation
Interviewer: Hi, thanks for joining us. To start, what’s your investing background, and how does it fit alongside your day job?
Manager: Sure. I’m an audit manager at Deloitte, so my day job is busy and very detail-oriented. Per policy, I don’t trade any securities of companies we audit or their relevant affiliates. My personal and household brokerage accounts are connected to our compliance system, and I run a pre-trade check against the restricted list before I place anything. Outside of that, I’m a personal investor who does day trading plus some swings, subject to those compliance checks and rules.
Interviewer: How did you first discover SimianX AI, and what made you try it?
Manager: I searched for “AI stock analysis.” I was tired of tab-hopping—news sites, charts, SEC filings, group chats—it was too much context switching. SimianX stood out because the multi-agent setup pulls public information into one place and summarizes the key points. I signed up that day.
Interviewer: How long have you been using it, and what’s your typical routine?
Manager: A few months now. Most trading days I’ll open it pre-market to scan setups. If I take a look mid-session, it’s on my own time and on my personal device, mainly to sanity-check a thesis. If I’m still holding something, I’ll do a quick after-hours pass for any new public filings or risk factors.
Interviewer: Any lines you’re especially careful not to cross?
Manager: A few hard lines: no MNPI—I only use public sources; no trading of Deloitte audit clients or relevant affiliates; pre-clearance/restricted-list check before any order; and trading is on personal time, on my personal device, never at the expense of client work. Depending on local policy, I also avoid restricted instruments like options or margin.
Interviewer: And what’s the payoff for you?
Manager: Speed with documentation. As an auditor, I care about evidence chains. SimianX helps me collect and organize public evidence faster, and I still make decisions only after compliance checks and my own risk rules.
Bold takeaway: SimianX AI user interview shows that speed + explainability unlock consistent intraday decisions.
Use Cases & Workflow
Interviewer: Which types of stocks do you typically analyze with SimianX? Can you give us some specific examples?
Manager: Mostly U.S. equities, with a tilt toward tech and semis. Two quick, compliance-cleared examples—just to illustrate my process, not advice. First, think of a large-cap chipmaker. I used SimianX’s multi-agent “debate” view to line up public news sentiment with what I was seeing on RSI divergence and the calendar for upcoming earnings. That helped me move faster on a small intraday entry—on my personal time and device, and after a restricted-list check—and I closed it green. Second, a mid-cap SaaS name—choppy tape, guidance chatter all over the place. SimianX pulled the public 8-K highlights together and surfaced insider transaction data plus a couple of clear risk flags. In that case, I didn’t take the trade. Sometimes the best trade is no trade.
Interviewer: Where does SimianX fit into your overall decision-making process?
Manager: It’s part of the core flow, but it’s not a “push-button” signal. I start with a quick screen—news flow, RSI/MACD, volume bursts—just to form a rough thesis. Then I toss the ticker into SimianX and get separate agent takes on technicals, fundamentals, news, and timing—all from public sources. What I really like is comparing the disagreements. If everything matches my view too neatly, I slow down—I don’t want to herd. When agents disagree, that’s my cue to dig deeper and test what I might be missing. And before any order, I run my pre-trade compliance check; if it’s not cleared or it’s on the restricted list, I pass.
Interviewer: What specific features do you find most valuable?
Manager: Number one is the multi-agent analysis—it shrinks my research time. After that, the risk sections, SEC/insider integration, and news aggregation are big time-savers. They also show confidence scores and a kind of AI consensus. I treat those like a thermometer—context, not commands. What matters is each agent’s independent reasoning so I can see the “why,” not just a score.
Interviewer: How did you handle analysis before SimianX? What pain points has it solved for you?
Manager: Pure manual grind. I was bouncing across news sites, multiple chart windows, digging through SEC filings, and texting trader friends. Lots of context-switching, easy to miss nuance, and it ate into my limited windows of personal time. With SimianX, I still make my own calls—no MNPI, no client names, compliance first—but the evidence-gathering is way faster and better documented.
Multi-Agent System Experience
Interviewer: How do you use the multi-agent analysis feature in practice?
Manager: I treat it like a panel of experts. One agent is pure technicals, another is fundamentals, another tracks news momentum and timing. I literally bookmark the disagreements—say the chart looks constructive but the news agent is flagging headwinds. That tension is where I slow down and dig. I want to see who’s citing what, and whether the evidence is current, public, and repeatable.
Interviewer: What's your take on the confidence scores and AI consensus features?
Manager: They’re a temperature check, not a trigger. Helpful for context, but I get more value from the agent-level evidence lists—timestamps, sources, and the exact item that flipped an agent’s view. It’s similar to audit work: consensus tells me the mood; the footnotes tell me the action. For example, if RSI is pressing sub-30 and there are public Form 4 insider buys, that goes on my watchlist—even if the overall consensus reads neutral.
Interviewer: That’s an interesting approach. Can you walk me through a recent example?
Manager: Sure—just an example, not advice, and definitely not a Deloitte audit client. So, one morning on my own time, I’m looking at a big U.S. tech hardware name. Before the bell, the technical agent is flashing this little RSI divergence and decent overnight volume. The news agent is more cautious—couple of public headlines about supply stuff and a peer’s guidance. Fundamentals look okay overall, but inventory turned the wrong way last quarter. The first thing I do is a quick restricted-list check in our system. If it’s not cleared, I’m done. It cleared, so I kept going. Then I pop open each agent’s sources—scan the articles, check the timestamps, skim the 10-Q/8-K sections it pointed to. All public. My rough plan was: “If the open holds above yesterday’s range and volume’s real, maybe there’s a small intraday bounce.” I set my lines: where I’m wrong, how long I’m willing to wait—tiny size. Market opens, price action doesn’t confirm. No shame—I skip it. Later the news agent pulls a fresh public note—a peer downgrade—which kind of validates the skip. Honestly, not taking it was the win. That’s pretty much my loop: agents disagree to I check the receipts to compliance check and only act if price and risk line up. Miss any piece, I’m out.
Product Value & Satisfaction
Interviewer: Since you started using SimianX, what's actually changed for you? Are we talking about speed, decision quality, returns? Anything you can quantify?
Manager: Speed is the clearest, most quantifiable improvement—especially on entry timing. I'm getting into positions faster with the same or better conviction. Quality is harder to put a number on, but my confidence level is definitely higher because I'm validating my thesis against these independent agent perspectives rather than just my own view or a single source. As for P&L and risk management, recent weeks have been net positive. But more importantly, I've avoided several bad trades because the risk section flagged regulatory issues or supply chain concerns that I would have completely missed on my own.
Interviewer: What do you like most about SimianX? And on the flip side, what still confuses you or feels like it's missing?
Manager: What I love most is the parallel agent debate structure is excellent—it gives me a PDF research report at the end. I get SEC and insider data visibility without having to hunt across multiple sites. The news summarization does a great job prioritizing actual market drivers over clickbait headlines. And crucially, risk management factors are surfaced before I enter the trade, not after. As for gaps—Ultra-short timeframes—like one to two-minute scalps—aren't really the product's edge yet. The reports can get pretty dense, and I'd love to see collapsible sections or a filter for "only show disagreements" between agents. And I'd appreciate more live-feed tempo for intraday triggers as they're happening.
Interviewer: That's helpful feedback. How would you summarize the before and after in your workflow?
Manager: Let me break it down for you. Before SimianX, discovery was this mess of juggling multiple tabs—news sites, charting platforms, everything scattered. Now it's all unified in one view: news, charts, SEC filings, everything I need. Validation used to mean texting friends or scrolling through forums for ad-hoc opinions. Now I'm getting structured debates between agents with actual evidence behind each view. The speed difference is huge. Those slow cross-checks between different sources? Mostly gone. I'm making decisions faster because I'm not constantly switching contexts. Risk assessment has completely flipped for me. I used to think about risk after I'd already formed my thesis on a trade. Now it's front-loaded—I see the potential scenarios and red flags right upfront before I do anything. And honestly, the biggest shift is in my trading discipline. I was definitely susceptible to FOMO before—you know, seeing something move and jumping in impulsively. Now I've built this habit of actively looking for contradictions first, which keeps me way more grounded. If I had to sum it up: this AI-powered multi-agent approach cuts through all the noise and genuinely speeds up my workflow—and I'm not sacrificing quality for that speed. Actually, I think my decision quality has improved.
Improvement Ideas & Future Direction
Interviewer: If you could add or change one feature right now—just one thing—what would it be and why?
Manager: A real-time trading assistant that refreshes every couple seconds with clear buy, sell, or watch signals. But here's the key part: I want a traceable trigger list showing me exactly which headline, which metric, what specific timestamp moved the needle. I need to see why the signal changed, not just that it changed.
Interviewer: Looking at the bigger picture—given your trading style and needs—where do you think SimianX should head next? What are the must-have features from your perspective?
Manager: I think there are three main pillars they should focus on. Live tempo and smart alerts. I'm talking about real-time triggers for price, volume, volatility, news, and SEC events. Ideally with voice or earpiece nudge alerts so I'm not glued to the screen all day. And integration—whether that's webhooks into my broker or a central alert hub I can customize. Second, research presets based on timeframe and style. Let me choose my trading window—ultra-short, short, medium, or long-term—and my strategy type, like momentum, valuation, or event-driven. Then have the system auto-tune the agent weights, the indicator packages, and even the report layout to match that profile. Third—and this is huge for me—deeper explainability for each agent. I want an evidence checklist with actual links, maybe screenshots, displayed on a timeline. Give me one-click cross-verification, like showing Form 4 insider buys aligned with price pivot points. And sensitivity testing: let me remove a headline or data point and see if the agent's view flips. The way I think about it: give me the why, not just the what. Evidence is the language of auditors, and honestly, it's the language of serious traders too.
Interviewer: That's really detailed feedback. It sounds like transparency and traceability are just as important to you as speed.
Manager: Exactly. Speed without understanding is just gambling faster.
Interviewer: Before we wrap up, is there anything else you'd like to share with SimianX users or the team?
Manager: I'm just excited to see where the product goes. The foundation is solid—it's already changed how I trade. If they can build out those live alerts and deeper explainability features we talked about, this could become genuinely indispensable for active traders.
Interviewer: That's great to hear. Thanks so much for taking the time to share your experience and insights with us today.
Manager: My pleasure. Happy to help.
Dialogue Recap by Topic
Background & Usage Motivation
A: Personal investor; audit manager at Deloitte. Been at it for years.
I only trade on my own time and personal device, and never in names audited by Deloitte or relevant affiliates.
A: Searched for AI stock analysis. Tried SimianX because it bundles multi-agent takes, SEC (public) filings, and news in one place.
A: A few months; most trading days; mainly pre-market and after-hours—and if I peek mid-session, it’s during personal breaks.
Usage Scenarios & Workflow
A: U.S. tech/semis. Two illustrative, compliance-cleared examples (not advice): a large-cap chipmaker I managed well intraday; a mid-cap SaaS I skipped after the risk call-outs.
Accounts are connected to our compliance system; I run a restricted-list check before any trade.
A: Hypothesis to Multi-agent check to Look for disagreements and make Decision. If it’s not cleared or price action doesn’t confirmed, I pass.
A: Multi-agent debate, risk sections, SEC/insider (public Form 4), and news aggregation.
A: Went from tab-juggling to one view of public evidence. Faster cross-checks, less noise.
Multi-Agent Experience
A: Like a panel. I flag the tension between agents—that’s my cue to dig.
A: Good thermometer. I still act on the agent evidence and my own risk rules.
Value & Satisfaction
A: Speed up, confidence up, and better risk-avoidance. I’m not chasing—contradictions keep me grounded.
A: Love the parallel debate and evidence links. Wish for collapsible sections, a “show disagreements only” toggle, and a snappier intraday feel.
Improvements & Future
A: A live assistant that surfaces traceable, public triggers—no auto-trading, just faster context.
A: More real-time context from public sources, research presets, deeper explainability, and an API for workflow (read-only / no order routing).
Table: Signals I Treat Differently (Audit Mindset)
| Signal | My Action | Rationale |
|---|---|---|
RSI < 30 + Form 4 buys | Watch/Scale-in | Confluence of momentum & insider confidence |
| Upbeat news + bearish agent | Read evidence | Avoid herd; examine counter-thesis |
| Consensus High, evidence thin | De-risk | Temperature ≠ proof; check the trail |
| SEC 8-K impact unclear | Stay flat | Price follow-through matters more than headlines |
“Contradiction awareness is my antidote to FOMO.”
Closing Thoughts
This conversation with a Deloitte audit manager highlights how multi-agent analysis and evidence-first design can genuinely accelerate day trading workflows without sacrificing discipline.
We've shared his feedback and feature suggestions with our product and engineering teams. His insights around real-time alerts, research presets, and enhanced explainability are already informing our roadmap as we continue to refine and develop SimianX AI for serious traders who need speed and substance.
