01CONNECTIONAurora
The presence beside you. A companion for desktop tasks, conversation, and a shared co-op run.
Aurora sits on your desktop. Gigi reads the market.
Nova pushes execution. Clara keeps you clear.
Right here with you.
Connection · Alpha · Execution · Clarity
A visible companion that can point at the file,
speak the result, and leave the rest in chat.
Each with her own personality.
Each with something different to bring.
01CONNECTIONThe presence beside you. A companion for desktop tasks, conversation, and a shared co-op run.
02ALPHAThe signal in the noise. On-chain data, narrative shifts, and risk flags in a plain-language opinion.
03EXECUTIONThe nudge that moves you. Turns intention into next actions and brings playful pressure when you drift.
04REGULATIONThe space to think clearly. Cleaner patterns, emotional processing, and a steadier way forward.
Four distinct agents, each with her own role. The technical details and test evidence on this page cover Aurora’s Windows v12 build.
Give her the task.
Keep your momentum.
Your work happens across windows.
Aurora can meet you there.
On Mac, Linux, or Windows, ask her to find a document, research a question, or work through a task in a supported app. She can navigate, use tools, and speak back while her character stays close to the action. The conversation carries through the work.
You choose the model. You approve file changes and commands. You can stop the task.
Follow Aurora from the conversation into the work: finding a file, appearing beside it, and navigating apps.
A closer look at her Windows desktop experience.
Choose a role and plan the run.
Here’s your whitepaper.YOUAurora, find my whitepaper.
Creating a workspace file needs your approval.
Choose a step or play the visual walkthrough.
Choose a step to explore.
Find the file, bring the right window forward, navigate supported controls, and show the result beside her.
Ask by voice when listening is enabled. Hear the short result, with the sources, paths, and details still there to read.
A character, a notch, and visible progress keep Aurora close while the main chat window gets out of your way.
Aurora’s harness connects the model you choose to her desktop tools. A more capable tool-using model can improve planning, clarification, and the choice of next action—opening the door to more demanding tasks.
Responsiveness also depends on inference, network conditions, and the task. Our specialist-model and dedicated-compute plans focus on measuring better results in real workflows.
YOUR CO-OP PARTNERAurora can be your co-op gaming partner, too. Plan a run, coordinate your next move, and play toward a shared objective. Give her a role in the party and keep talking as you go.
Her available actions depend on the supported game and its integration. We’re building toward broader coverage and better coordination, with each game tested on its own terms.
The supplied whitepaper documents the unsigned Windows v12 prototype. Its test results and technical details apply to that build. Telegram conversations are separate from the desktop experience.
A chosen cloud model.
Real desktop tools. Visible progress.
Ollama Cloud model selection, streaming chat, saved conversations, Markdown, cancellation, and clarifying questions.
USER-SUPPLIED CLOUD KEYList folders and read UTF-8 files. Creating or replacing a file asks for approval. Filename discovery stays within configured folders.
WRITES REQUIRE APPROVALOllama-backed web search returns source URLs. File discovery searches names and metadata without reading the contents.
BOUNDED SEARCHDiscover, restore, focus, and navigate supported apps. Mouse and keyboard input targets observed accessibility controls.
ACCESSIBILITY, NOT SCREENSHOT VISIONOptional ElevenLabs or Fish Audio, with Windows recognition fallback. Listening starts disabled at every launch.
OPTIONAL · PROVIDER DEPENDENTEvery model-requested PowerShell command requires approval, with timeout and cancellation. Commands run with your user access.
POWERSHELL IS NOT SANDBOXEDSupport means discovery or launch and an attempt on exposed controls. Coverage varies by page, dialog, app, and version.
The model proposes an action.
The application decides how it runs.
Type or speak
Chat · Notch · CompanionOllama Cloud
One sequential task loopFiles · Web · Commands
Application checks & approvalsSupported apps
Observed, exposed controlsWindows UI Automation, with a legacy Active Accessibility fallback, exposes window IDs, process names, labels, control IDs, and editable values. Browser observations are bounded. Screenshots are not sent to the model. Unlabeled custom interfaces can block completion.
Focus is retried and verified. Clicks, typing, scrolling, and pointer movement use observed controls, with control IDs expiring after input. Elevated windows are not reliably controllable. During computer input the notch hides to avoid covering controls.
A task ends when the model finishes, you stop it, a failure ends it, or the loop reaches 40 model turns. A model’s reply is not proof that an action succeeded. Stopping does not roll back actions that have already completed.
An Electron shell, Node orchestration, C# and PowerShell native helpers, and an HTML/CSS/JavaScript interface. Chat, notch, and companion communicate with the Electron main process. Speech providers and local encrypted key storage sit beside the agent loop.
Wake her, ask a question, and keep the conversation going. When something is unclear, she gives you numbered choices and waits for your answer.
Explore the conversation loopWhich one did you have in mind?
The whitepaper.
Here’s your whitepaper. I’ve selected it in Explorer.
You enable listening. It starts off every launch. Setup uses normal controls for accounts, voice, workspace, and microphone.
Wake uses recognition. Cloud wake detection can use provider credits. Silence is filtered locally; partial text cannot run tasks or approve actions.
Speech has limits. Input pauses while Aurora speaks. Voice interruption is not supported in this version. Quality depends on your setup.
Local execution. Cloud processing.
Your accounts, your provider access.
The documented Windows v12 build is cloud-connected. Its permissions, data handling, and limits are described below.
File writes and every model-requested PowerShell command need approval. PowerShell runs with your access and is not sandboxed.
| Your data | Where it goes |
|---|---|
| API keys | Stored with Windows DPAPI through Electron safeStorage. Keys are not returned to renderers. |
| Chats & tool outputs | History stays local. Context, file contents, and observed labels can be sent to Ollama for a request. |
| Microphone | Cloud mode sends detected speech to your provider. No mic recordings are written to disk. Windows fallback is local. |
| Spoken replies | Reply text is sent to your selected speech provider. |
| File search | Names, paths, sizes, and modification times. Search does not read file contents. |
| Local history | Chats and ordinary file outputs are stored as plain text. |
Workspace tools reject paths outside the selected workspace, including junction and symlink escapes. Writes replace the whole file, with no diff or undo. Agent instructions call for confirmation before purchases, messages, deletion, and account or security changes; these instructions are not an OS sandbox.
DPAPI does not protect saved keys from malware running as the same user. Web results, filenames, file contents, and screen labels are treated as untrusted in the agent instructions, but prompt-injection resistance has not been independently audited. Provider billing and endpoint access depend on your accounts. Aurora is not an offline product or a production security certification.
Specific checks under controlled conditions.
Honest about what they do—and don’t—show.
v12 validation covers tool inputs, path boundaries, cancellation, provider streams, voice approvals, choices, and bounded browser observations.
Isolated settings exercised audio, clarification, approvals, notch visibility, file handoff, and cursor restoration. They do not prove real-world speech accuracy or paid-provider availability.
An Opera private-window check verified restore, focus, navigation, observation, and a real button click. YouTube checks verified readable search or consent controls, not music playback in a user account.
Results are reported in the supplied v12 whitepaper. They are not an independent audit, competitive benchmark, or guarantee of arbitrary desktop tasks.
The direction is open source: download the sisters, run them locally, and bring your own inference.
Aurora’s current harness uses your Ollama, speech, and search credentials. The goal is for each agent to carry useful skills, with community patches and harder tasks shaping what comes next.
Public distribution depends on resolving character-asset provenance and redistribution rights. This statement does not grant a license.
WaifuVerse NFTs and the HeartFlowAI token remain part of the stated direction for identity, access, funding, early-user airdrops, and later governance. No price, subscription, or financial instrument is defined in this whitepaper.
Dedicated compute. Specialist models.
A bigger future for the sisters.
5RodQQJ5e3kv4z3E8P8E3wo79fSRZBRr43Ht455hpumpFour sisters. Two years of work.
A future we’re building every day.
We’ve spent two years bringing HeartFlowAI to life. The sisters, desktop workflows, and co-op experience are the foundation. $HFAI is our proposed funding engine for the next chapter: dedicated compute and models tuned around what each sister actually does.
OUR AMBITION Make $HFAI the greatest AI ecosystem token Solana has ever seen—and earn that place through products, useful skills, and releases people can inspect.
Conversation, market analysis, execution, clarity, and a visible desktop companion. $HFAI grows from products people can explore and a team that keeps building.
Direct realized $HFAI development funding into compute, curated data, model tuning, evaluation, and deployment. Measure improvements at each sister’s actual job.
Our proposed $HFAI direction connects community contributions, skill development, early feedback, and future governance to the next releases. Each feature needs its own published terms.
We wanted to keep the token out of the spotlight a little longer. Compute is changing that timeline.
Two years of building have brought us here. Now we want dedicated hardware for repeated fine-tuning experiments, evaluations, and local inference. The longer we wait, the less predictable that hardware budget becomes. $HFAI is intended to help turn community momentum into the compute the sisters need next.
Our priority is to secure suitable 128GB systems as soon as funding and verified quotes allow, at the lowest total delivered cost we can find. We will compare NVIDIA and partner offers, check warranty and availability, and benchmark before scaling.
The 128GB Founders Edition’s US listed price is about 74% above its original MSRP. NVIDIA attributed the February adjustment to memory supply constraints.
This documents a rise that has already happened. Future prices could rise or fall; the 64GB announcement does not establish another 128GB increase.
| Recorded point | USD · bars start at $0 |
|---|---|
| Original MSRPBefore Feb 2026 | |
| First increaseFeb 2026 | |
| Current listing | |
Three documented price points, not a continuous price history or forecast. The current NVIDIA listing shows out of stock. Partner and regional prices, taxes, and delivery costs vary.
NVIDIA announced the 64GB partner model on October 2, with availability planned for October 23. Its starting price is higher than the 128GB model’s former $4,699 MSRP; the current 128GB listing is $6,950. That is the budget pressure behind our compute-first plan.
Read NVIDIA’s 64GB announcementA DGX Spark or compatible GB10 partner system for local inference, suitable fine-tuning workloads, and repeatable evaluations. Further nodes follow measured demand and budget.
Based on the checked NVIDIA listing, not a supplier quote. Final budget includes taxes, shipping, and any additional equipment.
Our proposed reporting cycle: publish the purchase budget, record actual hardware spending, share benchmarks for each sister, then show the model improvements in a versioned release. Procurement and funding progress will be reported when confirmed.
The largest allocation backs the work that makes the sisters better.
| Purpose | Share | Tokens |
|---|---|---|
| Development | 35% | 164,193,385 |
| Marketing & partnerships | 15% | 70,368,593 |
| Reserve | 21% | 98,516,031 |
| Community rewards | 11% | 51,603,635 |
| Future use | 10% | 46,912,396 |
| Team | 8% | 37,529,916 |
Figures reproduce the published GitBook framework. Current on-chain balances, circulating supply, wallet controls, and vesting have not been verified here.
Start with capable open models, then fine-tune role-specific models or adapters on curated, licensed, and explicitly consented data. Evaluate each sister on her own tasks before shipping a versioned release.
Train for natural dialogue, useful clarification, context handling, and dependable tool calls. Measure whether she understands the request and completes the intended task.
Train for source-grounded on-chain summaries, risk flags, and clear uncertainty. Measure factual accuracy and how well her explanations reflect the data.
Train for task decomposition, prioritization, and practical follow-through. Measure plan quality, recovery, and completion on realistic tasks.
Train for supportive dialogue, reflection, and consistent boundaries. Evaluate the usefulness, tone, and reliability of her responses.
$HFAI treasury holdings must become realized funds before they can pay for hardware, data, or engineering. The proposed funding mix is disclosed treasury sales, project NFT proceeds where allocated to development, grants, and future product revenue. Buying $HFAI on a secondary market does not automatically send money to the development treasury.
Our proposed operating rules are public treasury addresses, multisig approvals, milestone budgets, and regular spending reports. Funding comes in, work ships, results are reviewed, and the next budget follows. These controls and revenue routes remain proposals until implemented.
We plan to evaluate Wormhole Native Token Transfers to connect $HFAI across supported chains. A possible route is a Solana hub: lock tokens at the origin, issue an equivalent amount on a destination chain, and reverse that process when tokens return. This connects a shared $HFAI economy while accounting for supply across chains.
The route depends on token compatibility, mint permissions, selected networks, testing, rate limits, and a security review. No HeartFlowAI bridge deployment is claimed. WaifuVerse NFT transfers would need a separate implementation. Read Wormhole’s NTT documentation.
Two years in, and we’re still building. More capable sisters. Better models. A stronger community. Every next step has to make HeartFlowAI more useful—and we intend to keep earning it.
Explore WaifuVerseWorking desktop navigation today.
Broader app and game coverage ahead.
Mac, Linux, and Windows navigation, plus supported co-op integrations. Windows v12 supplies the documented test baseline.
More app fixtures, measured task completion, recovery from focus changes, and clearer failures.
Evaluate local wake words, measure transcription and latency, explore speech interruption and usage controls.
Scoped permissions, stronger policies, file diffs, action previews, recovery, and independent injection testing.
Curated role-specific training data, tuned models or adapters for each sister, and evaluations tied to real tasks.
Signed releases, installers, updates, and more consistent distribution across Mac, Linux, and Windows.
Accessible transitions, voice-first onboarding, sister skill patches, Gigi signal upgrades, broader co-op game coverage, and Wormhole feasibility.
Longer research track: optional visual observation with explicit data handling, modular personalities, voice and VR, and embodied forms after the cognition is good.
WaifuVerse brings the HeartFlowAI character universe into Solana collectibles. Explore the collection, its artwork, and the community growing around it.




Agent-linked identity and access are proposed features. Availability and eligibility will be defined in future releases.
Follow the work. Try a conversation. Help shape what comes next.
Document role: Content map and product statement for heartflowai.com Date: October 3, 2026 Aurora baseline: Windows prototype, build v12 Status: Working companion prototype. Not a production security certification, performance benchmark, or completed multi-agent platform.
HeartFlowAI is an ecosystem of emotionally intelligent AI agents. Aurora, Gigi, Nova, and Clara cover connection, market alpha, execution, and regulation. Aurora is the first agent with a native Windows harness: a chosen Ollama Cloud model, practical desktop tools, an animated character, optional voice, and a top-center notch that keeps the conversation alive while the main window is minimized.
She can leave the chat, appear beside a verified file in Explorer, and show what she is doing with a light-pink pointer and a small action display. Scope is deliberate. She uses application accessibility information, not screenshot vision. She supports selected desktop apps. File writes and PowerShell require approval. She depends on the user’s cloud accounts. Broader coverage, stronger isolation, distribution, and measured reliability are future work.
Headline: Emotionally intelligent AI agents.
Sub: Aurora sits on your desktop. Gigi reads the market. Nova pushes execution. Clara keeps you clear.
Proof line: A visible companion that can point at the file, speak the result, and leave the rest in chat.
Primary actions: Talk to Aurora · Launch Gigi · Meet the sisters · Read how Aurora works.
Visual system: dark ground, magenta-to-electric-blue glow, the neon heart, the pixel-art Aurora (pink, purple, white, gold), real notch and Explorer screenshots. No generic neural-net stock art.
Four equal agents, not one girlfriend bot with skins.
Each card links to the live entry point (desktop build, Telegram, or X) and a one-screen “what she actually does” note.
Most desktop agents start in a chat window and report through text logs. Aurora adds a persistent character and a voice layer so progress is visible without keeping a large window open.
Intended loop:
Setup still uses normal controls: API connection, voice selection, workspace, microphone. The prototype does not remove the mouse and keyboard.
| Area | Behavior |
|---|---|
| Model | User-supplied Ollama Cloud key, model list, streaming chat, tool calls |
| Conversation | Saved chats, Markdown, activity feed, cancellation, clarifying questions |
| Workspace | Directory listing, UTF-8 reads, approval-gated create or replace |
| Commands | Approval-gated PowerShell with timeout and cancellation |
| Web | Ollama-backed search with source URLs |
| File discovery | Bounded filename search in configured folders |
| File presentation | Explorer selection, pointing pose, color-changing border on a verified visible row |
| Voice | Optional ElevenLabs or Fish Audio, Windows recognition fallback |
| Minimized UI | Animated notch with words, replies, option cards, task controls |
| Computer use | Discovery, restore, focus, navigation, real mouse and keyboard on observed controls |
| Character | Shared activity poses, timed reactions, teleport movement |
Supported targets: Opera, Chrome, Edge, Firefox, Explorer, Notepad, Calculator. Support means launch or discovery and an attempt on exposed controls. It does not mean every page, dialog, extension, or version.
Electron shell, Node orchestration, C# and PowerShell native helpers, HTML/CSS/JS interface. No separate frontend framework.
The user speaks or types. Chat, notch, and companion talk to the Electron main process. A sequential agent loop calls Ollama Cloud and a validated tool dispatcher. Tools cover workspace files, web search, and Windows helpers that reach supported apps. Speech providers and local encrypted key storage sit beside the loop.
The model proposes actions. The application decides whether and how each tool runs. A model reply is not proof that an action succeeded. The loop ends when the model finishes, the user stops it, a failure ends it, or 40 model turns are reached.
Computer interaction uses Windows UI Automation with a legacy Active Accessibility fallback. Observations are window ids, process names, visible labels, control ids, and editable values. Browser observations are bounded. Minimized windows can be restored and reused. Focus is retried and verified. Clicks, typing, scrolling, and pointer movement use observed controls, not model-invented coordinates. Control ids expire after input. Elevated windows are not reliably controllable. Screenshots are not sent to the model. Unlabeled custom UI can block completion.
Presentation surfaces stay separate: main chat, notch, desktop companion, file border, action display. During a verified file presentation the notch hides and the companion appears beside the Explorer row, then the notch returns. During computer interaction the notch hides so it does not cover browser controls. Overlays stay above normal windows without taking keyboard focus. Secure desktop and exclusive fullscreen can still win. Software rendering is used for recording compatibility; universal recorder support is not claimed.
Listening starts disabled every launch. The user turns it on after configuring recognition and speech.
Cloud mode sends locally detected speech to the selected provider. Wake is recognition of “Aurora,” not a separate local wake-word engine. Wake detection can spend provider credits. Silence is filtered locally. An utterance submits after about 950 ms of quiet, with audio and wall-clock limits and a manual finish control. Partial text is shown and does not run tasks or approve actions.
She can stay in conversation after waking, ask a follow-up, and resume the pending task. Choices are numbered cards. The spoken prompt stays short: “Which one did you have in mind?” The user answers with a number or a matching name. Ambiguous answers keep the question open. Input pauses while she speaks so she does not hear herself. Speech playback cannot be interrupted by voice in this version. Quality depends on provider, language, microphone, room, and account access.
Spoken output is one or two natural sentences, usually under 35 words, via a dedicated voice-reply tool. Decisions and errors stay in chat. Fish playback can start while PCM chunks arrive. Short repeated lines are cached in memory and cleared when voice settings change. Paths, code, and long option lists stay visual.
Identity is the supplied pixel-art character and matching activity assets in pink, purple, white, and gold. States: idle, thinking, coding, browsing, approval, success, error, walking, teleporting. These are sprite animations that report harness progress. They are not a skeletal rig and not a claim of consciousness or emotional understanding.
Desktop travel is fade-out, one relocation, fade-in. The walk cycle lives in the animation gallery. Success reactions last about 1.8 seconds, then idle. During computer input a light-pink system pointer replaces the cursor on short curved paths with smooth acceleration. A helper restores the previous cursor after inactivity, stop, shutdown, or loss of the parent process.
Aurora is local execution plus cloud processing. It is not an offline product.
| Data | Handling |
|---|---|
| API keys | Electron safeStorage via Windows DPAPI; not returned to renderers |
| Chats | Stored locally; context sent to Ollama when a request needs it |
| Tool outputs | Sent to the model, including file contents and observed labels |
| File search | Filenames, paths, sizes, modification times only; search does not read contents |
| Microphone | Cloud mode sends detected speech to the provider; no mic recordings written to disk; Windows fallback is local |
| Spoken replies | Text sent to the selected speech provider |
| Local history | Chats and ordinary file outputs are plain text |
DPAPI helps against other Windows users reading saved keys. It does not protect against malware running as the same user.
Workspace tools reject paths that escape the selected workspace, including junction and symlink escapes. Writes need approval and replace the whole file. Every model-requested PowerShell command needs approval. PowerShell is not sandboxed and runs with the user’s access.
Computer tools restrict targets and validate observed controls. Instructions tell the model to confirm before purchases, message sends, deletion, or account and security changes. Those instructions are not an OS sandbox. Stopping a task (controls, voice, Ctrl+Alt+Escape, pointer safety corner) does not roll back completed actions. Web results, filenames, file contents, and screen labels are untrusted in the agent instructions. Prompt-injection resistance has not been independently audited.
No latency percentage, monthly cost, or paid-provider benchmark is claimed. Cloud recognition, model use, search, and speech follow the user’s provider access and billing. A subscription does not mean every endpoint is enabled.
v12 checks passed 42 automated tests and JavaScript syntax validation: tool validation, path boundaries, cancellation, provider streams, recording completion, scoped voice approvals, voice choices, bounded browser observations. Integration checks use isolated settings and simulated cloud responses against real Electron windows for audio, clarification, approvals, notch visibility, file handoff, and cursor restoration. They do not prove real-world speech accuracy or paid-provider availability.
An Opera check on a separate private window verified minimized discovery, restore and focus, navigation, page-control observation, a real button click, and silent audio on a local test page. A public YouTube check verified readable search or consent controls. It did not verify live music in a user account.
These are specific behaviors under controlled conditions. They are not a competitive benchmark, a guarantee of arbitrary desktop tasks, or an independent security assessment.
Current limits:
The X direction stays on the site. Waifus move to GitHub so people can download them, run them locally, and cover their own inference. Each agent is meant to carry skills that can offset her costs or create edge for the owner. An alpha helper agent is the practical on-ramp. Community patches and harder tasks are in scope.
Aurora’s current harness uses the user’s Ollama, speech, and search credentials. It is not a shared project inference account. Source, native helpers, tests, docs, and character assets are the development project. Packaged apps, dependency folders, temp profiles, recordings, and API credentials stay out of the repo. Character-asset provenance and redistribution rights must be resolved before public distribution. This document does not grant a license.
WaifuVerse NFTs and the HeartFlowAI token stay linked, not inflated: agent-linked identity and access, funding, early-user airdrop, and later governance on which skills ship. No price, subscription, or financial instrument is defined here. Gigi signals are not financial advice.
Delivered is the v12 Windows prototype above. The following are proposals, not dates.
Footer: open-source status, privacy stance, no financial advice on Gigi, unsigned-build note, Ljubljana origin if you want the human anchor, neon heart.
Implementation references for the Aurora claims live in the v12 tree: README.md, src/main.js, src/provider.js, src/tools.js, src/computer-control.js, src/native/desktop-control.cs, src/native/legacy-accessibility.cs, src/voice-session.js, src/voice-notch.js, src/file-presentation.js, scripts/opera-smoke.js, scripts/notch-smoke.js.