# Codyco: AI reservation completion for hotel groups

Canonical: https://mudpie.ai/companies/codyco/
Breadcrumb: [Home](https://mudpie.ai/) / [Companies](https://mudpie.ai/companies/) / [Codyco: AI reservation completion for hotel groups](https://mudpie.ai/companies/codyco/)
Author: Ali Abouelatta (https://mudpie.ai/authors/ali-abouelatta/)
Published: 2026-09-19
Updated: 2026-09-19
Research type: Company profile
Method: Company and accelerator sources checked 2026-09-19. Product claims are attributed to their sources; this is research, not a hands-on product trial.

Codyco is an AI reservation team for hotel groups that want missed calls to become completed bookings rather than voicemail. Its product promise is specific: answer the guest, resolve the request, take payment when appropriate and write the confirmed reservation into the property-management system.

## What it does

The [current Codyco site](https://www.codyco.ai/) says the system answers around the clock, handles questions, reservations, payments and invoices, and writes confirmed bookings directly into a PMS. It publicly confirms end-to-end booking workflows with Oracle OPERA Cloud, Sihot and Apaleo, while other PMS integrations are assessed against the required workflow. Hotels can decide which requests Codyco completes and which require a live transfer or structured handover.

The homepage shows €10,000-plus in bookings written into the PMS, 63% fewer rings at the front office, a 98.3% satisfied-caller rate and zero missed calls. Those are company-presented figures, not an independent hotel-performance study. The [YC launch](https://www.ycombinator.com/launches/Oe7-codyco-ai-receptionists-for-hotel-groups) reports a €5,000 additional-booking example for a 53-room hotel in four weeks and says the product worked with seven hotel groups at launch. A time-limited ambassador offer appears in that older launch, but current public base pricing is not published.

## Why I’d look closer

The buyer is a multi-property hotel group with overflow, after-hours or international call volume. The founders’ backgrounds fit the integration problem: YC describes Stefan Schaff’s data and AI leadership on large Siemens programs, Endrit Bytyqi’s data-platform work, and Alexander Schober’s experience turning an enterprise proof of concept into a larger initiative.

The advantage is completion. A voice layer that only answers is still another queue; Codyco’s value is the PMS write-back and handover. The tradeoff is that a booking is a financial and guest-experience commitment. Payment errors, rate-plan confusion, cancellations, accessibility requests and exceptions need a visible route to staff.

## What I’d ask

Which rate, inventory, cancellation and payment rules are enforced in each PMS? Can staff review every write-back and recover a failed booking? How does Codyco handle multilingual guests, group bookings, loyalty benefits and fraud signals? What does “satisfied caller” measure, and how are missed calls counted across forwarding and overflow?

## My editorial take

Shortlist Codyco if missed hotel calls are a measurable direct-booking leak and your PMS is supported. Start with overflow calls and a limited booking policy, then reconcile every reservation and payment against the PMS before expanding to changes, invoices and complex requests. The product earns its keep at the point where the call becomes a correct record.

## Quick facts

| Field | Sourced detail |
| --- | --- |
| Product | AI hotel reservation, guest-question, payment and PMS workflow |
| Buyer | European hotel groups and multi-property hospitality teams |
| PMS support named | Oracle OPERA Cloud, Sihot and Apaleo |
| Pricing | Current base pricing not published; older launch offer was time-limited |
| Main question | Does Codyco complete a correct booking, not just answer the phone? |

## Sources checked

| Source | Checked |
| --- | --- |
| [YC company profile](https://www.ycombinator.com/companies/codyco) | 2026-09-19 |
| [Codyco homepage](https://www.codyco.ai/) | 2026-09-19 |
| [Codyco blog](https://www.codyco.ai/blog) | 2026-09-19 |
| [Codyco YC launch](https://www.ycombinator.com/launches/Oe7-codyco-ai-receptionists-for-hotel-groups) | 2026-09-19 |

## Cohort context

Codyco is listed in Fall 2025. In our 2026-09-18 directory snapshot, 90 of 146 listed companies in that cohort have YC’s primary industry label B2B (61.6%). This is a current-directory comparison, not an original intake count or a performance ranking. [Nine-cohort dataset](https://mudpie.ai/research/yc-cohorts-2026-09-19.json).

## Public website snapshot

Observed 2026-09-19T16:14:58.079Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.

| Signal | Homepage observation |
| --- | --- |
| Product description metadata | Observed |
| Canonical link | Observed |
| H1 or H2 heading | Observed |
| Typed structured data | Observed |
| Docs/developer link | Not observed in this response |
| Pricing link | Not observed in this response |
| llms.txt link | Observed |
| Markdown alternate | Not observed in this response |

[Public observations](https://mudpie.ai/research/yc-homepage-links-2026-09-19.json) · [Collection method](https://mudpie.ai/research/yc-homepage-methods/README.md). Missing links here do not establish that a capability or file is absent elsewhere.


## Author disclosure

I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.