Pre-Seed· Private beta· Founder-led pilots
Turn missed paid leads into booked jobs.
Bazas is the AI front desk for service businesses. It answers calls and messages, qualifies leads, books jobs within owner-defined rules, and preserves the full customer context.
Informational only. Not an offer to sell or a solicitation to purchase securities.
Platforms
The browser-based Bazas workspace is available at app.bazas.ai for signup, workspace creation, billing, and selected CRM workflows. Feature availability varies by plan and founder-led onboarding.
Bazas CRM Mobile is being tested through TestFlight. It is not yet publicly available on the App Store — public submission is planned after release-readiness, privacy, billing, and App Review checks are complete.
Not on the App Store yet. Status reviewed Jul 22, 2026.
The problem
Service businesses already pay for leads. They still lose them.
- A customer calls or sends a message.
- The owner or dispatcher is busy — driving, on-site, or with another customer.
- The response is delayed.
- The customer contacts the next provider.
- The business loses both the lead cost and the potential job revenue.
What the leak looks like
Adjust the inputs for a rough sense of the money at stake when inbound isn't answered fast.
Illustrative estimate only. This calculator does not represent actual or guaranteed Bazas customer results. Values are computed in your browser and are not sent anywhere.
The product
One AI front desk across every customer conversation.
A lead comes in on any channel. Bazas answers, qualifies, applies the owner's rules, books or escalates, and writes it all down.
Feature availability was reviewed on Jul 21, 2026. Access to beta features is currently limited to selected private-beta customers.
Live · Beta · Planned
What works today, and what doesn't yet.
Generally available (0)
- None yet — see roadmap.
Available in selected private beta (9)
- SMS & text intakeSelected pilot customers
- AI voice answeringSelected pilot customers
- Email intakeSelected pilot customers
- Lead qualificationSelected pilot customers
- Service-area checksSelected pilot customers
- Appointment bookingSelected pilot customers
- Human handoffSelected pilot customers
- CRM timeline & customer memorySelected pilot customers
- Follow-up automationSelected pilot customers
Founder-assisted (1)
- Lead-source integrationsSet up per customer during onboarding
Demo
See one lead move from first contact to booked job.
A short walkthrough of the inbound workflow is available on request while the product is in private beta.
A product walkthrough is available to qualified investors on request. The interface preview on this page is illustrative, not a live production screenshot.
Request a walkthroughTiming
Why now
Several shifts make an AI front desk viable for small service businesses today, not five years ago.
Customers increasingly expect an immediate response and move on quickly when they don't get one.
Service businesses buy more of their leads through paid digital channels.
Inbound demand is fragmented across calls, texts, email, and lead marketplaces.
AI voice and language quality has improved enough for real customer conversations.
Modern APIs let voice, messaging, scheduling, and CRM connect in one workflow.
Labor and administrative costs for a dedicated front desk remain high.
We attach a primary source to any external market statistic before showing it, rather than citing round numbers.
Early evidence
We show evidence, not adjectives.
Traction figures carry a period, an as-of date, and a methodology. Until those are published, we state the stage honestly.
Dated metrics — pilots, leads processed, response time, takeover rate, and revenue — are shared with qualified investors in the data room, each with its methodology.
Results to date come from Repair ASAP, the founder's own service business — a real-world operating test environment, i.e. internal operating validation, not yet independent third-party validation. Each figure is defined by a period and a methodology and is verifiable in the investor note / data room.
Business model
Subscription revenue plus usage-based expansion.
A monthly subscription includes defined AI, voice, and messaging allowances. Revenue can expand through higher usage tiers, overages, additional users, and additional locations.
- Monthly subscription per business
- Included AI, voice & SMS allowances
- Usage overages beyond the plan allowance
- Higher usage tiers
- Additional users
- Additional locations
- Premium workflows
- Financial operations module
- Agency & franchise plans
- White-label
- Enterprise integrations
Usage economics expand revenue with adoption
Plans include AI, voice, and messaging allowances. As a business relies on Bazas more, revenue expands through higher tiers, overages, and added users or locations — usage-based expansion on top of the base subscription.
Blended gross margin and the economics of usage above cost are shared with qualified investors in the unit-economics data room, not asserted publicly.
Only current and genuinely planned lines are shown. Not every line generates revenue today. Investor-facing economics (ARPA, gross margin, retention) are shared in the data room.
Market
Start narrow: U.S. home-service businesses that already pay for leads.
Bazas initially targets U.S. home-service businesses with 1–20 field workers that already pay for leads and depend on fast customer response.
Initial ICP
Bottom-up sizing
- Count businesses in the selected verticals.
- Take a realistic share at the target size band.
- Apply a realistic annual revenue per account.
- That yields an initial serviceable revenue opportunity.
- Expand later through multi-location, agencies, and franchises.
We do not claim the entire SMB or global AI market. Sizing is bottom-up and shown with its inputs.
Go-to-market
Founder-led today; repeatable and channel-driven next.
Phase 1 — Founder-led
Live- Direct sales
- Industry relationships
- Pilot onboarding
- Manual configuration
- Product feedback
- ROI validation
Phase 2 — Repeatable vertical motion
Planned- Vertical playbooks
- Outbound
- Referrals
- Agency partnerships
- Industry communities
- Integration partners
Phase 3 — Channel expansion
Planned- Marketing agencies
- Franchise networks
- Multi-location operators
- White-label partners
- Lead-gen platforms
- Telecom partners
Channel statuses are stated honestly: a relationship counts as a partnership only when it is live, not when there is potential interest.
Land & expand
Land on inbound. Expand into the system of record.
Expansion is intended to increase retention, switching costs, ARPA, and data quality. These are goals, not yet proven — switching costs depend on retention data we are still gathering.
Competition
An honest competitive map.
Service businesses already stitch together tools and staff to handle inbound. Bazas competes with each of these categories — and with doing nothing.
| Category | Voice answering | SMS & email | Lead-source intake | Owner-defined rules | Scheduling | Human takeover | CRM memory | Field-service workflows | Financial ops |
|---|---|---|---|---|---|---|---|---|---|
| Bazas | ◑ | ◑ | ◑ | ● | ◑ | ● | ◑ | ○ | ○ |
| FSM suites | ○ | ◑ | ◑ | ◑ | ● | ● | ● | ● | ● |
| CRM tools | ○ | ◑ | ◑ | ◑ | ◑ | ● | ● | ○ | ◑ |
| AI receptionists | ● | ◑ | ○ | ◑ | ◑ | ● | ○ | ○ | ○ |
| Answering services | ● | ○ | ○ | ◑ | ◑ | ● | ○ | ○ | ○ |
| DIY stack | ○ | ◑ | ○ | ○ | ◑ | ● | ◑ | ○ | ○ |
Bazas
- ◑Voice answering
- ◑SMS & email
- ◑Lead-source intake
- ●Owner-defined rules
- ◑Scheduling
- ●Human takeover
- ◑CRM memory
- ○Field-service workflows
- ○Financial ops
FSM suites
- ○Voice answering
- ◑SMS & email
- ◑Lead-source intake
- ◑Owner-defined rules
- ●Scheduling
- ●Human takeover
- ●CRM memory
- ●Field-service workflows
- ●Financial ops
CRM tools
- ○Voice answering
- ◑SMS & email
- ◑Lead-source intake
- ◑Owner-defined rules
- ◑Scheduling
- ●Human takeover
- ●CRM memory
- ○Field-service workflows
- ◑Financial ops
AI receptionists
- ●Voice answering
- ◑SMS & email
- ○Lead-source intake
- ◑Owner-defined rules
- ◑Scheduling
- ●Human takeover
- ○CRM memory
- ○Field-service workflows
- ○Financial ops
Answering services
- ●Voice answering
- ○SMS & email
- ○Lead-source intake
- ◑Owner-defined rules
- ◑Scheduling
- ●Human takeover
- ○CRM memory
- ○Field-service workflows
- ○Financial ops
DIY stack
- ○Voice answering
- ◑SMS & email
- ○Lead-source intake
- ○Owner-defined rules
- ◑Scheduling
- ●Human takeover
- ◑CRM memory
- ○Field-service workflows
- ○Financial ops
Bazas is early: several capabilities are partial and in private beta. Mature suites lead on breadth, invoicing, payments, mobile apps, and integrations. ● Yes · ◑ Partial · ○ No.
Where incumbents lead
- Established brand and trust
- Broad field-service functionality
- Mature mobile apps
- Invoicing and payments
- Large integration ecosystems
- Large support organizations
Where Bazas is different
- AI-native inbound workflow
- Unified context across calls and messages
- Owner-defined operating rules
- Faster configuration for lead handling
- One timeline across every channel
- Focus on converting inbound leads into booked work
- A path to operational memory as the system of record
Defensibility
Where a moat could come from — and where it doesn't exist yet.
Founder–market fit
Built from inside the workflow.
Bazas was founded by Nikita Lylov, an economist and service-business operator who has worked with CRM systems since 2011—first in sales, later as an entrepreneur and business owner, and now as the founder and product builder behind Bazas.
After launching Repair ASAP, a home-services company in New York City, he experienced the problem firsthand: paid leads arriving while the team was out on jobs, conversations fragmented across calls, SMS, email, Yelp, and Thumbtack, and valuable customer context getting lost between first contact, booking, and follow-up.
Bazas was developed and tested inside that live operating workflow. Repair ASAP—a founder-operated service business—is Bazas's first operating customer and real-world test environment. Bazas is a separate SaaS platform being built for the broader service-business market.
Working with CRM systems since 2011 across sales, entrepreneurship, and home-services operations. Built Bazas from a live operating business and continues to test it against real leads, calls, bookings, and follow-up workflows.
Bazas is founder-led today. The Pre-Seed round is intended to support key hires across product, engineering, security, and customer success.
Roadmap
Now, Next, Later — targets, not guarantees.
Now
- Web app (private beta)
- iOS app (TestFlight testing)
- Current integrations
- Reliability
- Onboarding
- Measurement
Next
- iOS release candidate + App Review submission
- Repeatable onboarding
- Channel integrations
- Reporting
- Paid customer growth
Later
- Public App Store release
- Multi-location
- Agencies
- Franchises
- Financial operations
What this round is meant to prove
The round
We're raising a Pre-Seed round.
- Company stage: Pre-Seed, founder-led, private beta.
- The round funds the milestones below and the use-of-funds categories shown.
- Round terms are shared with qualified investors after securities-counsel review.
Round details available to qualified investors. This is not an offer to sell securities.
Use of funds
Category intent shown below. Exact percentages and dollar amounts are set once the budget is approved and are shared with qualified investors.
| Product & engineering | Reliability, integrations, and onboarding. |
| Customer onboarding & success | Get pilots live and retained. |
| Go-to-market experiments | Find a repeatable acquisition channel. |
| Infrastructure & AI/telephony | Voice, messaging, and inference at target cost. |
| Legal & compliance | Corporate, securities, and data compliance. |
| Security | Tenant isolation, audit, and vendor review. |
| Operating reserve | Runway buffer. |
Key risks
The risks, in plain sight.
Mitigations reduce risk. They do not eliminate it.
Product reliability
ProductAI can misunderstand a customer, make a mistake, or miss important information.
Customer adoption
MarketSome owners may not trust AI to interact with their customers.
Competition
MarketMature FSM and AI-receptionist companies could add similar capabilities.
Unit economics
EconomicsVoice, SMS, AI, and support costs could compress gross margin.
Platform dependency
TechnicalBazas depends on third-party APIs, telecom, messaging, and lead-source integrations.
Execution risk
CompanyA Pre-Seed company has limited team and capital.
Data & privacy
SecurityThe system processes conversations and customer data.
Fundraising risk
CompanyA future round may not close on the desired timeline or terms.
FAQ
Investor questions, answered.
What exactly does Bazas do?
Bazas is an AI front desk for service businesses. It answers inbound calls and messages, qualifies the job, books within the owner's rules or escalates to a person, and keeps every interaction in one CRM record.
Who is the initial customer?
U.S. home-service businesses with roughly 1–20 field workers that already pay for leads and depend on fast response — repair, cleaning, HVAC, plumbing, electrical, and similar.
What is live today?
The product is in private beta with founder-led onboarding. Availability varies by feature — the inbound workflow (voice, messaging, qualification, booking, CRM) is available to selected pilot customers today. See the product status section for the generally-available / private-beta / planned breakdown.
What is still in beta?
Most of the inbound workflow — voice answering, messaging intake, qualification, booking, and CRM memory — is in private beta with selected pilot customers.
Does Bazas replace office staff?
No. It handles inbound when no one can, and hands off to a person with full context. The owner can take over any conversation at any time.
Can a business take over a conversation?
Yes. Human takeover is a core design principle, not an afterthought.
How does Bazas avoid incorrect bookings?
Bookings run inside owner-defined rules — service area, availability, and job-acceptance criteria. When rules aren't met, it escalates rather than guessing.
Which channels does Bazas support?
Calls, SMS, and email, plus lead-source integrations set up per customer during onboarding. Coverage varies by third-party API limits.
How does Bazas make money?
A monthly subscription that includes defined AI, voice, and messaging allowances. Revenue expands through higher usage tiers, overages, additional users, and additional locations — and over time into premium workflows and financial operations. Blended economics (ARPA, gross margin, retention) are shared with qualified investors in the data room.
What is the current pricing model?
Subscription plus usage. Public plan details live on bazas.ai. Blended economics for investors are shared in the data room.
What is the current company stage?
Pre-Seed, founder-led, in private beta.
Is Bazas generating revenue?
Revenue status is shared with qualified investors. The public site does not display unverified financial figures; dated figures are available in the data room.
How many pilot customers are active?
The current count and related metrics are shared with qualified investors with an as-of date and methodology.
What is the go-to-market strategy?
Founder-led sales today, moving to repeatable vertical playbooks and then channel partners (agencies, franchises, multi-location, white-label).
Who are the main competitors?
Field service management suites, CRMs, AI receptionists, human answering services, DIY stacks, and in-house staff. See the competition section for an honest, category-level comparison.
Why won't established CRM companies simply copy this?
They may add similar features. Our intended edge is focus, an AI-native inbound workflow, owner-defined rules, unified context, and vertical playbooks — advantages we are still proving.
What is the long-term product vision?
An operating system for small and mid-sized service businesses — starting at inbound and expanding into the system of record.
What legal entity is raising the round?
Bazas AI LLC is the operating company. The definitive issuing entity for any offering — which may be Bazas AI LLC or a related entity — is set out in the offering documents provided to qualified investors.
Who owns the intellectual property?
IP ownership is documented in the data room (IP assignment and corporate documents).
What investment instrument is being used?
Instrument and round terms are shared only with qualified investors and only after securities-counsel review.
How will the funds be used?
Product and engineering, onboarding and success, go-to-market experiments, infrastructure, legal/compliance, security, and an operating reserve. Category intent is shown; exact allocation is shared with investors.
What must the company prove before the next round?
Reliable inbound workflows, measurable customer outcomes, a repeatable acquisition channel, and unit economics within target. See milestones.
What are the primary risks?
Product reliability, adoption, competition, unit economics, platform dependency, execution, data/privacy, and fundraising. See the risks section — we do not hide them.
How can an investor access the data room?
Request materials through the form. Access is reviewed individually and may require identity or investor-status verification.
How frequently are investor materials updated?
Materials carry a last-updated date. Investor updates are posted as milestones are reached.
Is the information on this website an investment offer?
No. This website is for informational purposes only and is not an offer to sell or a solicitation to buy securities. Any offering, if made, will be conducted only through definitive offering documents and in accordance with applicable law.
Review the product, evidence, and current round materials.
Requests are reviewed individually. Access to certain materials may require identity or investor-status verification.