Aster: The AI That Guides Every User to the Right Outcome

See It In Action

Same engine. Every industry.

Pick a tab. Watch Aster guide a completely different user to a completely different outcome. The same platform underneath every time.

What you're watching: A B2B buyer just landed on the site. Aster qualifies them in real-time, scoring lead intent, routing to the right rep, all without a single form field.

What you're watching: A patient describes symptoms on a mobile app. Aster asks targeted follow-up questions and determines urgency level, no human triage required.

What you're watching: A customer hits an issue. Aster diagnoses the problem via voice, resolves it in-context, and only escalates when genuinely needed.

What you're watching: A homeowner starts an insurance quote. Aster infers details from context, skips redundant questions, and reaches a quote in half the usual steps.

What you're watching: A SaaS user hits a drop-off point. Aster surfaces a smart survey at the right moment, asking only what it doesn't already know from their behavior.

💻 Desktop Chat Widget

B2B SaaS: Inbound Lead Qualification

Hey! I see you're exploring our platform. What's the core challenge you're trying to solve?

Our SDRs spend 70% of their day on leads that never convert. We need to automate the initial qualification.

Single Select

What's your monthly inbound lead volume?

Under 500

500 - 2,000

2,000 - 5,000

5,000+

Multi Select

Which tools are in your current stack? (select all that apply)

HubSpot

Salesforce

Outreach

Zapier

Custom / Internal

At 2-5K leads with HubSpot + Salesforce, you're leaving ~450 SQLs/mo on the table. Last one:

Single Select

What's your timeline for implementing a solution?

Next quarter

Within 30 days

Just exploring

✓ Score: 0.96 · High-intent Enterprise lead. Routed to Sr. AE Sarah Chen with full context brief + ROI model.

📱 Mobile iOS App

9:41 ●●●● 📶 🔋

Hi, I'm here to help you figure out the right level of care. Can you describe what you're experiencing?

I've had a persistent headache for 3 days, and this morning I noticed some blurred vision in my left eye.

Slider

On a scale of 1-10, how severe is the headache right now?

1 - Mild710 - Worst

Multi Select

Are you experiencing any of the following?

Light sensitivity

Throbbing pain

Worse when standing

Neck stiffness

Nausea / vomiting

If you have a photo of your eye condition, share it here:

📷

left_eye_redness.jpg

Image Upload Mild redness around iris

I can see conjunctival injection. Combined with your profile, this warrants urgent evaluation.

⚠ URGENT
Neurology appt auto-scheduled: Dr. Patel at 2:30 PM.
Image + symptom summary forwarded to provider.

‹ Back Step 1 of 5

📎

Describe symptoms...

▲

🎤 Voice / IVR Interface

🎤 SaaS Platform: Billing & Churn Prevention LIVE

Voice conversation in progress

02:34

Live Transcript

AI Hi! How can I help you today?

You I want to cancel my subscription. The reporting features are way too basic for what we need.

AI I'm sorry to hear that. Before I process anything, what kind of reporting are you looking for that's missing?

You We need cohort analysis and custom dashboards. Right now we're exporting everything to Google Sheets.

AI Interesting, we actually shipped cohort analysis and a custom dashboard builder in our v3.2 update three weeks ago. It's under Analytics, then Advanced. Can I check which plan you're on?

You We're on Growth. Wait, really? We didn't see any announcement about that.

AI Growth plan has full access! I just enabled a guided walkthrough. Want me to schedule a 15-minute session with our analytics specialist?

You That would be great actually. Let's hold off on the cancellation.

✓ Churn prevented. Feature discovery gap resolved. Walkthrough enabled, specialist session booked.

📋 Adaptive Form / Survey

Auto Insurance: Adaptive Quoting

0 / 4

QUESTION 1 OF 4

What vehicle are you looking to insure?

2023 Tesla Model 3 Long Range

✓ Auto-detected: Autopilot, AEB, 5-star NHTSA, safety section skipped

QUESTION 2 OF 4

What is your ZIP code?

90210

QUESTION 3 OF 4 · DYNAMICALLY ADDED

Beverly Hills has elevated Tesla theft risk. Where is the vehicle stored overnight?

Private garage

Covered parking / carport

Street parking

Apartment complex lot

This question was added because ZIP 90210 flagged high theft risk

QUESTION 4 OF 4

Which coverage types do you want in your quote?

Comprehensive

Collision

Liability

Roadside

Uninsured Motorist

✅

$156/mo

4 coverages · 92% confidence

4 questions asked vs. 18 industry standard $23/mo savings from garage offset

📊 In-App Widget: Product Survey

Triggered by behavioral signal

📊 Reports usage: daily → 0 sessions (28 days). Memory loaded.

Hey Alex, you used to open Reports every day, but we haven't seen you in there for a month. What happened?

The new layout is confusing. I can't find where my saved reports went.

Single Select

Which part trips you up the most?

Finding saved reports

The new filter panel

Exporting & sharing

Navigating between views

Slider / Scale

How likely are you to recommend us to a teammate right now?

0: Not at all610: Definitely

Got it, sounds like a discoverability issue, not a fundamental problem. I'm flagging this for your CSM Jamie. She'll send a quick walkthrough. Does that work?

Yes, that works!

✓ Feature confusion identified (not churn intent) · NPS 6 flagged · CSM walkthrough queued

Core Innovation

The Optimizer Function

The optimizer tells Aster: "given what we know, are we done, or what should we ask next?" It's the pluggable brain that makes Aster work across any domain.

Three ways to define your optimizer

Use our pre-built scoring functions, connect your own API, or build one visually. Mix and match across projects.

⚙

Built-in

Pre-built optimizers for lead scoring, triage, readiness assessment. Start in minutes.

🔌

Bring Your Own (API)

POST to your endpoint. Aster sends collected answers, you return a score + signals.

✎

Visual Builder

Drag-and-drop DSL editor. Define rules, weights, thresholds visually. No code required.

BYOF API Contract

// Aster calls your API after each answer
POST your-api.com/optimize

{
  "session_id": "abc-123",
  "answers": [
    {"q": "Team size?", "a": "50"},
    {"q": "Budget?", "a": "$500/mo"}
  ],
  "context": {"source": "website"}
}

// Your API responds with:
{
  "score": 0.82,
  "ready": false,
  "signals_needed": ["timeline"],
  "suggested_priority": ["timeline"]
}

Optimizer functions by domain

Lead QualificationMQL Score → 0.0-1.0

Support TriageSeverity → L1/L2/L3

Insurance QuoteConfidence → 0.0-1.0

Medical TriageUrgency → 1-5

Marketplace MatchReadiness → 0.0-1.0

Recruiting ScreenFit → Pass/Fail/Maybe

Brand Voice ComplianceTone Score → 0.0-1.0

🎤

Optimizers aren't just for outcomes, they enforce your brand too

Upload your brand guidelines and Aster ensures every conversation sounds like you. Tone, vocabulary, values, content standards, all verified through automated evals before and during deployment. Learn more →

Multimodal Intelligence

Aster doesn't just ask questions. It reasons over what it sees.

Most conversational tools only understand text. Aster processes images, documents, structured selections, sliders, and voice, then reasons over them to make smarter decisions in real-time.

👁

Vision Reasoning

Users upload photos, documents, or screenshots. Aster doesn't just store them, it reasons over visual content to extract signals, detect patterns, and inform the next question.

Example: Patient uploads eye photo → Aster detects conjunctival injection → escalates to urgent triage. Insurance customer uploads damage photo → Aster assesses severity → adjusts quote.

🎮

Adaptive Input Selection

Aster dynamically chooses the optimal input type per question, free text when context is ambiguous, radio buttons for constrained choices, sliders for scales, chip-select for speed.

Example: Pain severity → Slider (precise). Symptoms → Multi-select (efficient). Timeline → Chip-select (fast). Open complaint → Free text (expressive).

📈

Cross-Modal Reasoning

Aster fuses signals across modalities. An image, a slider value, a selection, and free text aren't separate inputs, they're combined into a unified context that drives the optimizer.

Example: Eye photo (visual) + pain slider 7/10 (structured) + "3 days" (text) + photophobia (multi-select) = unified clinical picture → urgent routing decision.

How Multimodal Reasoning Works

💬

Text Input

Free-form NLU

📷

Image Input

Vision model

🎧

Voice Input

Speech-to-text + tone

☑

Structured Input

Select, slider, chips

❯

🧠

Fusion Engine

Unified context

❯

🎯

Optimizer

Score + next action

All modalities flow into a unified context that the optimizer scores holistically, not as separate channels. This is how Aster detects conjunctival injection from a photo and cross-references it with a pain score of 7/10 to make an urgent routing decision.

Persistent Memory

Aster remembers every user

For use cases with repeat users, Aster integrates with our memory infrastructure, or yours, to learn preferences, history, and context over time. Every return conversation starts smarter than the last.

🧠

Aster Memory Layer

Use our built-in memory infrastructure. We store user preferences, interaction history, and learned context. Zero setup required.

🔌

Bring Your Own Memory

Already have a user profile system, CRM, or data warehouse? Plug it in via API. Aster reads from your memory layer at session start.

☤

Healthcare

Remembers patient history, medications, allergies, past visits. No repeating yourself every appointment.

"I see you're still on lisinopril 10mg from your last visit. Has anything changed with your blood pressure?"

💬

Customer Support

Knows past tickets, resolution history, account tier, and previous frustrations. Skips "tell me your issue from scratch."

"Welcome back, Sarah. I see you had a billing issue last month that we resolved. Is this related, or something new?"

💰

Financial Advisory

Tracks risk profile, life events, portfolio preferences over time. Advice evolves as circumstances change.

"Last time we spoke, you mentioned planning for your daughter's college in 2028. Want to revisit that allocation given the recent market shift?"

🎓

Education

Tracks mastery levels, learning pace, preferred explanation style. Each session adapts to where the student left off.

"You nailed quadratic equations last session. Ready to tackle polynomial factoring, or want a quick warm-up first?"

User Memory Timeline: Sarah M. (Support)

Jan 15

First Contact

Signed up for Growth plan. Primary use: team reporting. 12-person team. Preferred communication: concise, no fluff.

Feb 3

Support Ticket

Billing issue, double charged. Resolved with refund. Frustrated tone. Flagged: sensitive to billing topics.

Feb 28

Feature Request

Asked about cohort analysis. Noted: exports to Google Sheets. Power user behavior. Likely upgrade candidate.

Mar 12

Today's Session

Aster loaded full memory before conversation started. Knew about billing sensitivity, feature gap, and communication preference. Adapted tone and approach accordingly.

How Memory Flows Into Each Session

①

User starts session → Aster fetches memory profile (ours or yours via API)

②

Memory injected into system prompt: preferences, history, known signals, sensitivities

③

Optimizer skips questions already answered in prior sessions → fewer questions, faster outcomes

④

After session, new learnings written back to memory: updated preferences, new signals, outcome data

⑤

Next session starts with richer context. Conversations compound in quality over time.

Privacy-first by design

Memory is scoped per user, per project. Full GDPR/CCPA compliance. Users can request memory export or deletion. Data encryption at rest and in transit. Enterprise customers can self-host the memory layer.

Brand Intelligence

Every conversation sounds like you

Upload your brand guidelines and Aster ensures every question, response, and interaction reflects your brand's tone, style, values, and personality. Verified continuously through automated evals.

📄

Upload your brand guidelines

Drop your brand book, style guide, tone of voice document, or content standards. Aster extracts and applies them automatically.

PDF DOCX Notion Figma URL Plain Text

🎤

Tone & Voice

Formal vs. casual, warm vs. direct, playful vs. professional. Aster calibrates every generated question and response to match your voice spectrum.

📝

Vocabulary & Terminology

Your preferred terms, banned words, industry jargon, product names. "Customers" not "users." "Team members" not "employees." Always enforced.

🎯

Brand Values & Guardrails

What your brand stands for. Topics to avoid. Sensitivity guidelines. Inclusive language requirements. All baked into the system prompt and validated in evals.

📈

Content Design Standards

Question length limits, reading level targets, formatting rules, emoji usage, sentence structure preferences. Your content design team sets the rules, Aster follows them.

Same question. Different brands.

Generic AI

"Please provide your annual revenue range so we can determine the appropriate pricing tier for your organization."

With Brand Voice (Casual SaaS)

"Roughly how big is the team? No need to be exact, just helps us figure out the best plan for you."

Generic AI

"What is the nature of your medical complaint today?"

With Brand Voice (Healthcare)

"Tell me what's been bothering you. Take your time, the more detail you share, the better I can help guide you to the right care."

How evals enforce brand compliance

Brand Profile Generation

Aster parses your uploaded guidelines into a structured brand profile: tone vectors, terminology dictionary, value constraints, and content rules.

System Prompt Infusion

Brand profile is woven into the system prompt that drives question generation. Every LLM call carries your brand DNA as a first-class constraint.

Automated Brand Evals (every deploy)

Before any flow goes live, Aster runs a brand eval suite: synthetic conversations scored against your guidelines by an LLM-as-judge. Checks tone, vocabulary, values compliance, reading level, and sensitivity.

Continuous Monitoring

In production, a sample of live sessions is scored on brand adherence. Drift alerts fire if scores drop. Auto-refinement adjusts prompts to stay aligned.

Brand Scorecard

Dashboard showing real-time brand compliance across all your deployed flows. Drill into individual sessions. Export for your brand team's review.

96%

Tone Match

100%

Terminology

98%

Values Aligned

Grade 8

Reading Level

Investor Information

Building the intelligence layer for a $26B+ market

Aster is creating a new category at the intersection of forms/surveys ($4.7B), conversational AI ($13.9B), and lead generation ($7.5B). We're the intelligent backend these markets are missing.

The Raise

$4M

Seed Round

18mo

Runway

$1M ARR

Target @ Month 12

Use of Funds

55% Engineering & Product

20% Go-to-Market & Sales

15% AI/ML Research

10% Operations & Legal

Market Opportunity

$4.7B

Survey & Forms Market¹

$13.9B

Conversational AI Market²

$7.5B

Lead Gen Software Market³

Aster sits at the convergence layer, providing the intelligent backend that all three markets need but none of the incumbents provide. The combined TAM is $26B+ and growing at 17%+ CAGR.

Target Unit Economics

85%+

Gross Margin⁴

140%+

Net Revenue Retention⁵

<12mo

CAC Payback Period

Go-to-Market Roadmap

Phase 1: Wedge

Months 1-6

Lead qualification (B2B SaaS)
Customer intake (marketplaces)
Free tier + PLG motion
"Replace Typeform" migration
HubSpot / Salesforce integrations

Phase 2: Expand

Months 6-18

Customer support triage
Insurance, healthcare, legal
Enterprise sales motion
Optimizer marketplace launch
BYOF and visual builder

Phase 3: Platform

Months 18-36

Federated learning network
Developer ecosystem + open SDK
White-label / embedded Aster
Global expansion
$10M ARR target

Competitive Landscape

No incumbent occupies the "intelligent, outcome-optimized, domain-agnostic backend" position.

Player	Intelligence	Outcome-Driven	Domain-Agnostic	Self-Improving
Typeform / SurveyMonkey	✗ Static	✗ Data collection	✓	✗
Qualtrics	~ Basic branching	~ Post-hoc analytics	✓	✗
Intercom / Drift	~ Some AI	~ Sales-focused	✗	✗
Sprig / Braze	~ Event triggers	✗ Data collection	~ In-app only	✗
Qualified	✓ AI-native	✓ Pipeline	✗ B2B only	✗
Aster	✓ AI-native	✓ Optimizer-driven	✓ Any domain	✓ Federated

The Moat: Compounding Intelligence

More deployments → more Q/A data → smarter models (via federated learning) → better outcomes → more deployments. This flywheel compounds over time and cannot be replicated without the network.

Additional moats: Optimizer marketplace (network effects), trained domain QA models (switching cost), accumulated Q/A corpus (data asset), and first-mover category definition.

Comparable Companies

Company	Seed Round	Current Valuation	Category
Typeform	$1.5M (2014)⁶	$935M (2022)	Forms / Surveys
Qualified	$12M Series A (2019)⁷	$600M+ (2022)	Conversational Sales
Forethought	$9M (2018)⁸	$300M+ (2023)	AI Customer Support
Qualtrics	Bootstrapped	$12.5B (2023 acquisition)	Experience Management

Sources & Footnotes:

[1] Grand View Research, "Online Survey Software Market Size, Share & Trends," 2024. Global market valued at $4.7B, CAGR 14.6% through 2030.

[2] MarketsandMarkets, "Conversational AI Market," 2024. Projected $13.9B by 2025, growing at 21.8% CAGR.

[3] Grand View Research, "Lead Generation Solution Market Size," 2024. Global market at $7.5B, CAGR 17.5%.

[4] Comparable SaaS gross margins: Twilio 51% (2024), Datadog 80%, Snowflake 73%, Stripe ~85% (est.). Aster's API-first model with minimal COGS targets 85%+. Source: Public company filings (SEC 10-K/10-Q).

[5] Usage-based expansion benchmark: Top quartile PLG companies average 130%+ NRR. Source: OpenView Partners, "2024 Product Benchmarks Report."

[6] Crunchbase: Typeform, Inc. Funding history. Seed round May 2014.

[7] Crunchbase: Qualified.com, Inc. Series A November 2019.

[8] Crunchbase: Forethought, Inc. Seed round November 2018.

[Problem slide sources] SurveyMonkey, "Survey Completion Rate Benchmarks," 2023 (33% avg). Gartner, "Voice of the Customer Survey Benchmarks," 2024 (25% CSAT response rate). MarketingSherpa, "Lead Generation Benchmark Report," 2023 (79% of marketing leads never convert to sales). Forrester Research, "The State of Conversational AI," 2024 (adaptive flows show 2.4x completion lift).

Get in Touch

investors@withaster.ai

Most users never reach their"aha moment."Aster makes sure they do.

Week 1 is where you lose them.

Most leads go cold before your SDR calls.

Wrong intake means wrong care.

Confusing quotes lose buyers mid-flow.

Embed

Define your outcome

Every user, guided

Optimizer: Lead Readiness

Signals Collected

Aster Health

Optimizer: Clinical Triage Severity

Clinical Signals (multi-input)

Live Transcript

Optimizer: Retention Triage

Signals

Optimizer: Quote Confidence

Signals

Optimizer: Churn Prediction

Memory Context Loaded

Signals

Outcome-driven, not answer-driven

Adapts to each user, not one-size-fits-all

Self-improving, not set-and-forget

Three ways to define your optimizer

Built-in

Bring Your Own (API)

Visual Builder

BYOF API Contract

Optimizer functions by domain

Vision Reasoning

Adaptive Input Selection

Cross-Modal Reasoning

Aster Memory Layer

Bring Your Own Memory

Healthcare

Customer Support

Financial Advisory

Education

User Memory Timeline: Sarah M. (Support)

How Memory Flows Into Each Session

Upload your brand guidelines

Tone & Voice

Vocabulary & Terminology

Brand Values & Guardrails

Content Design Standards

Same question. Different brands.

How evals enforce brand compliance

Brand Profile Generation

System Prompt Infusion

Automated Brand Evals (every deploy)

Continuous Monitoring

Brand Scorecard

Same questions for everyone. No learning. No intelligence.

Every question earned. Every answer drives the outcome.

Lead Qualification

Customer Support

Customer Intake

Sales Discovery

Insurance & Finance

Healthcare Triage

Education

Recruiting

In-App Product Surveys

Starter

Growth

Enterprise

Data Network Effects

Federated Learning

Optimizer Marketplace

Multimodal Reasoning

Brand + Memory Lock-in

Your users deserve better thana one-size-fits-all experience.

Get Early Access

You're on the list, friend.

Building the intelligence layer for a $26B+ market

The Raise

Market Opportunity

Target Unit Economics

Go-to-Market Roadmap

Most users never reach their
"aha moment."
Aster makes sure they do.

Your users deserve better than
a one-size-fits-all experience.