Clara AI companion for consultants

Clara prepares the work. The judgment remains yours.

Clara organizes sources, surfaces gaps and contradictions, and turns materials, conversations, and data into presentations, documents, and analyses for review. Clara works with you inside Codex.

36-second overview Watch: from project materials to a decision-ready presentation

Create or correct high-impact HTML decks and PowerPoint presentations.

Run interviews and turn recordings into reviewed transcripts.

Map retail attributes and compare new products and best sellers with the rest of the assortment.

Analyze Excel, CSV, and Parquet files with checked calculations and charts chosen to fit the question.

Create or correct a presentation in your corporate style

Describe the result you want. You can start from the project materials or an existing presentation.

New presentation

Start from the project materials

Add Word, PDF, and PowerPoint documents, images, spreadsheets, notes, or recordings. State the audience, objective, and duration: Clara proposes the structure and prepares the presentation.

"Create a 20-minute presentation for this audience from the materials in this folder."

Existing presentation

Correct what needs changing

Write the corrections or record them aloud. Clara updates a copy and checks that everything else remains unchanged.

"Record my feedback, apply it to a copy, and leave everything else unchanged."

Visual references

Match your visual style

Add a PowerPoint template, reference presentation, logo, or brand guidelines. Clara uses them for layout and style.

"Use this PowerPoint as the visual reference for the new presentation."

Choose the deck format

Both formats are editable. Choose PowerPoint when the file must be opened and reworked in PowerPoint; choose an HTML deck for interactivity, navigation, and animations.

An editable PowerPoint

A .pptx file that can be opened and edited in PowerPoint. Choose it when you must follow an existing template or hand the file to someone else to edit.

"Deliver an editable PowerPoint and check every slide."

An interactive HTML deck

A self-contained 16:9 HTML deck with speaker notes, fullscreen mode, keyboard or touch navigation, and animations. It does not require PowerPoint.

"Deliver an interactive HTML deck with speaker notes."

Open the project folder and describe what you need

Write in your own words: you do not need to learn commands. No separate API key is required; model work uses your existing ChatGPT plan.

Gather the project materials Put documents, presentations, data, images, notes, or recordings in the folder, then open it in Codex."Use Clara in this folder."
Describe what you want to achieve Explain what you need, who it is for, and in which format. For a presentation, also state the duration."Create a 20-minute editable PowerPoint for this audience."
Identify the content and style to follow Identify which documents to use for the content and which template or presentation to use for the style."Use this Word file for the content and this PowerPoint for the style."
Review and correct Open the result and describe the changes in your own words. Clara works on a copy and checks the updated version."Shorten slide 4 and add my contact details to the last slide."

Where Clara processes data

Vera and Clara follow the same two-category policy. The distinction depends on the processing boundary, not on the profession.

Work inside Codex

Ordinary plugin functions

Vera and Clara do not automatically anonymise data. They may use local Python to filter or aggregate information when useful.

Data supplied to the model is processed through the user’s existing ChatGPT plan. Ordinary workflows do not send client files, prompts, or model-context content to Mparanza.

Each workflow is mapped when it is added or changed: what normally stays local and what Codex may read. No record is created for each prompt.

Mparanza-hosted service

A separate processing boundary

Remote Interview, Transcription/Voice Capture, and the retail-data service are hosted by Mparanza. The content needed for those functions reaches Mparanza systems and, where required, OpenAI services.

Each hosted service is documented once at service level, including access and retention or deletion arrangements. There is no prompt-by-prompt documentation.

Watch the data-handling video

The project is not just a presentation

Clara organizes sources, distinguishes facts, inferences, and professional judgment, and surfaces gaps and contradictions. You decide what goes into the client materials.

Sources and conclusions stay connected

Clara makes it clear what comes from the documents and what comes from interpretation or professional judgment.

What is missing stays visible

Clara keeps missing information, contradictions, and pending decisions visible.

Pick up where you left off

Reopen the same folder in a new Codex session and continue from the materials, notes, and drafts already there.

From product data to a checked retail report

Retailer Signals compares new products and best sellers with the rest of the assortment. Brand Fit relates those signals to the brand's presence and catalogue. Retail data and reviewed mappings use a Mparanza-hosted service; product images and generated reports are saved in your project folder.

Use the data already available in the Mparanza-hosted retail service. Clara starts with the records for the selected retailer and category. The installed version does not yet collect new data from retailer pages.

Standardize and verify the attributes. Clara maps the values to a common taxonomy; a second review checks the mappings.

Compare the groups. New products are those the retailer presents as new. Clara compares new products and best sellers with the rest of the assortment using checked calculations.

Create the report. Clara saves an HTML report on your computer and checks its calculations, readability, and appearance.

Retailer Signals

For one retailer and category, compare new products and best sellers with the rest of the assortment and generate a verified report.

Brand Fit

It starts with a verified Retailer Signals analysis and compares the assortment findings with the brand's presence at the retailer and its catalogue. It uses stored data, not a live shelf check. The comparison is presented in a report.

Interviews, documents, and data analysis

Clara conducts interviews, transcribes recordings, prepares working documents, and analyzes business data.

Remote interview

Conduct an interview with a dedicated link

The participant opens a Mparanza-hosted link without signing up. Mparanza and OpenAI process the audio and answers to conduct and transcribe the adaptive interview. The interview record remains hosted until manual or administrative deletion; link expiry is not deletion.

"Prepare a 15-minute interview in Italian for this participant."

Transcription

Transcribe a meeting or recording

Record the conversation or upload an existing audio file through Mparanza-hosted Voice Capture. The audio reaches Mparanza and OpenAI for transcription. Hosted working files are deleted before the completed bundle is returned; Codex may then read the local transcript for speaker attribution and review.

"Transcribe this recording and identify the speakers."

Advisory work

From sources to a document for review

Using the documents, notes, and conversations in the project folder, Clara prepares a first draft as a Word document or presentation and flags what is missing before review.

Sources, open questions, and versions are stored in the project folder. Content Codex interprets may enter the model context through your ChatGPT plan.

"Organize the sources, identify what is missing, and prepare a Word document for review."

Business data

From data to a clear answer

Start with an Excel, CSV, or Parquet file and describe the business question. Clara chooses the analysis, runs checked calculations, creates the most useful chart, and explains the result.

"Analyze this spreadsheet, choose the most useful chart, and explain the result."

See Clara at work

Short guides to Clara's main capabilities, narrated in the language of this page.

Install Clara and open your first project

You can find Clara in the OpenAI Marketplace. After installation, open the project folder in Codex and describe the result you want to achieve.

  • Open Clara's official OpenAI Marketplace page.
  • Start the installation from the page.
  • Open Codex, go to Plugins, and confirm that Clara is installed and enabled.
  • Open the project folder and describe what you want to achieve.
If installation does not work
Installation is not available Confirm that you are signed into OpenAI, then reopen Clara's official page.
Clara does not appear Confirm that Clara is installed and enabled, then open a new Codex chat in the project folder.

"Use Clara in this folder."

Not signed in? ChatGPT asks you to sign in, then opens Clara's listing.