Babav Beta
Sovereign & on-prem Become a Steward Access Babav.ai

Experts' knowledge,
at your fingertips.

Imagine the leading specialists across the fields that matter to you each sat down and poured everything they know — every framework, every hard-won lesson, every "here's how I'd actually handle this" — into one place you can talk to, any time. That's Babav.

Try a Sphere · $25 Become a Steward
babav.app / chat
Live demo
Curated AI
Trusted  ·  Grounded  ·  Open
Analyze RacerJet AG's cloud spend 2023–2025 and quantify savings.
FinOps Sphere · Claude Opus 4.5 Grounded · 0.96
Executive Cloud Cost Assessment — RacerJet AG
€2.91M
3-yr spend
€519–721K
savings p.a.
18–25%
reduction

Concentration risk: VMware accounts for 96% (€2.8M) of spend — the principal cost lever12.

Phase 1 · 0–3 mo · €80–120K — RIs, idle cleanup, O365 audit
Phase 2 · 3–6 mo · €400–600K — VMware rightsizing, legacy OS
Phase 3 · 6–12 mo · €200–350K — cloud-native shift3
3 curated sources read aloud ↓ download as PDF
Erfolgsquote von Eigenbedarfskündigungen zugunsten der berufstätigen Tochter — nach Begründungstiefe?
Legal-DE Sphere · Claude Opus 4.5 Grounded · 0.94
Eigenbedarfskündigung — § 573 Abs. 2 Nr. 2 BGB
26
Entscheidungen
BGH+BVerfG
gestützt
§ 573 / § 574
BGB

Ehrliche Grenze: Belastbare statistische Erfolgsquoten liegen in der Datenbank nicht vor — aus den ausgewerteten Entscheidungen lassen sich jedoch belastbare qualitative Muster ableiten1.

+  Konkrete Familiengründung / Ausbildungsort  ·  überwiegend erfolgreich2
−  Pauschale „Lebensplanung" ohne Substanz  ·  häufig gescheitert
−  Hohes Mieteralter + angespannter Markt  ·  Härteeinwand greift3
3 curated sources read aloud ↓ Rechtsanalyse als PDF
Ask for Babav advice…
Agent: Babav — Standard / Confidential
Curated AI — answers signed by named experts
i.

What you get.

An AI trained by the people who actually lead in their field, using their own materials — the frameworks, case files, and know-how they've built over years of doing the work. Not generic answers scraped off the internet. The real thing.

ii.

How to use it.

You don't need to be an AI expert. You don't need to figure out the "right" way to ask, or learn any tricks. Babav comes with a library of prompts and context chains — pick the situation you're in, and the right questions are already there waiting for you. No blank page. No guesswork.

iii.

When you want a human.

Babav also opens the door to the expert networks behind the platform. Whenever you want to talk to a real person, they're one step away.

What Babav is

A knowledge brain
that owns its sources.

Every document — any format, anyone's archive — funnels into one curated, retrievable, expert-signed knowledge brain. One source of truth, owned by the Steward, queried by you.

i. inputs any document,
every format.
ii. ingestion
Babav AI. the knowledge brain
Who answers, when you ask

Named experts
behind every Sphere.

A name. A face. A specialty. A reputation at stake. When the assistant reaches the edge of its corpus, you don't see a fallback model — you see the expert who built it.

Steward · Curated Active
Prof. Dr. Markus Pflügl
Prof. Dr. Markus Pflügl, LL.M.
Curator — German Legal Sphere
12
context chains
250,000
assets
Steward · Curated Active
Erik Norman
Erik Norman
Curator — FinOps Sphere
3
context chains
5
tools
59
assets
Steward · Curated Active
Jeroen Hendriks
Jeroen Hendriks
Curator — GTM Sphere
2
context chains
84
assets
More Stewards in private beta Get access to an expert, if AI hits a wall
How

A knowledge layer
that compounds.

Every great chat becomes context. A sequence of contexts becomes a Context Chain. Every Context Chain lives in your Library.

In practice

32 steps. 30 minutes. One Investor Committee-ready memo.

Spheres come pre-loaded with Context Chains — guided sequences the Steward authored from real practice. Run one and Babav walks you step-by-step. Your version is saved. The next chat starts where the last one stopped.

▶ Context Chain in progress · Babav Investor Journey
Investor Journey, in motion.
Start manually from… ›
Run automatically from… ›
Phase 1Initial Screening Report
Phase 2Market Validation & Partnership Analysis
Phase 3Comprehensive Due Diligence
Phase 4Investment Committee
Phase 5Term Sheet & Partnership
Phase 1 of 5 · Initial Screening Report Step 1 / 6
01Executive Summary — thesis alignment, advance / decline / watch02:14
02Team Assessment — founder evaluation matrix03:48
03Market Opportunity — TAM, competitive landscape, timing04:12
04Traction Validation — acquisition metrics, growth, PMF04:50
05Risk Assessment — red flags, regulatory, competitive threats02:30
06Thesis Fit & Recommendation — final fund-fit scoring01:20
32 steps
expert-sequenced · 5 phases
~30 min
total runtime · resumable
Step 1 of 4 · Create context A Steward starts with a Context — a single curated unit of knowledge and prompt.

Create Context

Create a new context with name, description, prompt, and optional documents.

Investor Journey
Comprehensive seed-stage diligence — 32 steps across 5 phases.
You are an expert investment analyst. Using available Babav materials from the datastore (pitch deck, business plan, founder bios)…
Account Context Community Context

Add Context Chain to "Top-Level"

Create a new context chain with a sequence of context steps.

Babav Investor Journey
Top-level context chain for seed-stage diligence — five phases: Initial Screening, Market Validation, Founder Deep-Dive, Financial Diligence, Final IC Decision.

Edit Inline Context

Edit the inline context details and manage documents.

STEP 1 — EXECUTIVE SUMMARY — Initial Screening Report (Steps 1–6)
Top-line investment read on Babav: thesis alignment score, Advance/Decline/Watch call, and 3 bullets of supporting rationale.
You are an expert investment analyst. Using available Babav materials from the datastore (pitch deck, business plan, founder bios), generate an Executive Summary with:
No documents attached.
⋮⋮ PHASE 1:  INITIAL SCREENING REPORT (Steps 1–6) 6 steps
STEP 1 — EXECUTIVE SUMMARY inline
Top-line investment read: thesis alignment, advance/decline/watch call.
↗✎🗑
STEP 2 — TEAM ASSESSMENT inline
Founder and team evaluation matrix scoring experience and skill.
↗✎🗑
STEP 3 — MARKET OPPORTUNITY inline
TAM sizing, competitive landscape, market timing, entry barriers.
↗✎🗑
STEP 4 — TRACTION VALIDATION inline
Acquisition metrics, growth trajectory, product-market fit indicators.
↗✎🗑
STEP 5 — RISK ASSESSMENT inline
Red flags, regulatory exposure, competitive threats with risk rating.
↗✎🗑
STEP 6 — THESIS FIT & RECOMMENDATION inline
Final fund-fit scoring and IC-ready recommendation.
↗✎🗑
⋮⋮ PHASE 2:  MARKET VALIDATION & PARTNERSHIP ANALYSIS (Steps 7–12) 6 steps
Every chat persists. Every Context Chain resumes. Nothing starts cold again.
The numbers are the design

Monetize your
expertise.

Your career, encoded. Honest split, public math.

The split

Half the subscription fee.

Babav provides the AI backbone, the payments, the discovery surface, the retrieval pipeline. You provide curation and judgment. The split is honest and the math is public.

up to
50%
Subscription fees
$25 / month

Premium (Curated AI and Tools) Service Subscription. Recurring. Paid monthly.

Worked example · 400 subscribers · 3 published Tools · model your own →
~$205,680/ year
Recurring
Part-time
Maintained alongside primary work
Earnings trajectory

Curate once.
Compound forever.

Subscribers
compound
Tools published
multiply
HIGH MID LOW INFLECTION third Tool ships M01 M06 M12+
Passes Tool PPU Subscriptions
Apply to become a Steward Model your earnings
Sharper architecture · sharper answers · sharper economics

Every AI subscription hides a second invoice — hours verifying, tokens retrying, trust eroding.
Babav is built so the invoice you sign is the invoice you pay.

The industry press calls it TIBS — token incremental burn syndrome — bills that inflate with no anchor to value.1 Babav was built the other way round: per-Sphere pricing, grounded generation, persistent corpora.

What I want to do
Babav
the platform
LLM A
leading frontier model
LLM B
leading frontier model
LLM C
leading frontier model
Grounded factuality
Trust the answers — traceable to source.
✓
Single-digit hallucination
#1 on Google's FACTS · grounded by design
×
10%+ on enterprise docs2
Worse in reasoning mode
×
10%+ on enterprise docs2
Worse in reasoning mode
×
13.6% on enterprise docs2
Worse in reasoning mode
Honest limits
If the Sphere can't support an answer, it says so.
✓
"No answer possible"
Refuses ungrounded answers by design
×
Guesses to satisfy the prompt
Confabulation is the default mode
×
Guesses to satisfy the prompt
Confabulation is the default mode
×
Guesses to satisfy the prompt
Confabulation is the default mode
Persistent context
Every doc, every chat, ready anytime.
✓
Built for this
Knowledge persists across every session
×
Each chat is blank
No persistent corpus
×
Each chat is blank
No persistent corpus
×
Each chat is blank
No persistent corpus
Upload my entire library
Thousands of files. Gigabytes of data.
✓
5 GB included, expandable
Per private domain · cryptographically segregated
×
~50 files per chat
Gone afterward
×
~20 files per chat
30 MB cap each
×
Session-scoped uploads
Lost between sessions
Flat, predictable price
No bill surprises.
✓
$25 / $99 per domain
Unlimited use · volume discount up to 35%
×
Token-metered
Bill drifts with use
×
Token-metered
Bill drifts with use
×
Token-metered
Bill drifts with use
Earn from my expertise
Get paid when others use my knowledge.
✓
50% / 60% / 55% share
Subscriptions · Tool PPU · Tool passes
×
No revenue share
—
×
No revenue share
—
×
No revenue share
—
Truly private data
Never used for training. Fully isolated.
✓
Isolated by default
Customer-owned datastores
!
Opt-out or paid tier
Default is often open
!
Opt-out or paid tier
Default is often open
!
Opt-out or paid tier
Default is often open
Worked example
Run a legal Sphere
3.5M pages, ~7 GB, 5-step context chain, persistent.
3.5M pages ~7 GB · ~2.1B tokens 5-step context chain Persistent forever
$99 / month flat
Not possible
Not possible
Not possible
✓ Yes ! Partial × No
1 Rupert Goodwins, "AI quota inflation is no token effort. It's baked in", The Register, 20 April 2026.
2 Vectara HHEM Leaderboard, enterprise-length · 2026 — Gemini 3 Pro 13.6%, Claude Sonnet 4.5, GPT-5, Grok-4 all above 10%. Source values reflect public leaderboard at time of publication.
Flat. Transparent. Scaling with depth.

Pricing.
Pay for expertise, not tokens.

Explorer
Free
No credit card
Access to all free services
Curated
$25 / mo annual
$30 / mo monthly
Access to premium service.
Custom
$99 / mo annual
$119 / mo monthly
Curate your own private AI.
Composite
$25 / mo annual
Available at 2+ Spheres
Unified intelligence layer across your active Spheres.
Sponsored
Free to user
By contract — funded by sponsor
Brand sits in a knowledge context · curation preserved.

Example — the Fractional Professional

3 Curated AI Services + 1 Custom Sphere = 4 Services. For $174 a month: access to premium service across four Spheres, the full Library, unlimited Context Chains — Composite available the moment your knowledge universe is ready.

3 Curated Services (3 × $25)$75.00
1 Custom Sphere$99.00
Total monthly$174.00
No tokens. No caps. No per-seat licenses. No paid POCs. No six-figure floors.
Strategy Studio · By invitation
For organizations that want to co-design their knowledge architecture with us.
A selective surface where a handful of strategic partners co-design a dedicated, sovereign knowledge environment directly with Babav's founders — tacit expertise made explicit, owned and run by you.
Sovereign & on-prem →

Three doors. One platform.
Pick the one with your name on it.

Babav is in private beta. Reach out by the door that fits — we reply within two business days.

For the curious
Try a Sphere  $25
Unlimited queries, grounded sources, the named expert behind every answer.
Access Babav.ai
For the expert
Become a Steward
Up to 50% of subscription fees. Package your experience into an AI service — alongside the work you already do.
Apply to steward
For the brand
Sponsor a Sphere
Reach engaged audiences inside trusted expert channels. support@babav.com
Contact Babav