ChatGPT + veriova

Give your Custom GPT a persistent memory that survives across conversations. No coding required-everything is done inside ChatGPT's GPT Builder.

What you'll get

After following this guide, your Custom GPT will be able to:

  • Automatically remember important decisions, conventions, and lessons from your conversations
  • Recall past context when you ask about something you discussed before
  • Generate briefings-ask “catch me up” and get a summary of everything it knows
  • Share knowledge across your team if multiple people use the same GPT

How it works (simple version)

veriova acts as a “brain” that sits behind your GPT. When you tell ChatGPT something important, it saves it to veriova. When you ask a question, it checks veriova first to see if it already knows the answer.

ðŸ-¬

You chat with GPT

Tell it decisions, rules, or facts

🧠

GPT saves to veriova

Automatically stores the important bits

-Ϭ

GPT remembers forever

Recalls context in future conversations

Step 1: Sign up for veriova

Go to veriova.com/signup and enter your email. You'll receive a magic link-click it to verify.

After verifying, you'll see two things you need to save:

  • API Key-starts with cv_ (save this immediately, it's shown only once)
  • Project slug-a short name like my-project

Step 2: Create your Custom GPT

In ChatGPT, go to Explore GPTs -†- Create. Switch to the Configure tab.

Name your GPT something descriptive, like “My Project Assistant” or “Team Memory Bot”.

Step 3: Add the Instructions

Paste the following into the Instructions box. This tells your GPT how to use veriova:

GPT Instructions
You are a project assistant with persistent memory powered by veriova.

## MEMORY PROTOCOL

### Auto-Store (use the "pushMemory" action)
Automatically store memories when you:
- Make or discuss an important DECISION (type: "decision")
- Establish a CONVENTION or coding standard (type: "convention")
- Discover a reusable PATTERN (type: "pattern")
- Learn a LESSON from a mistake or debugging (type: "lesson")
- Write a useful code SNIPPET (type: "snippet")
- Reference external docs or URLs (type: "reference")

For each memory, choose a clear title and detailed content.
Set importance 1-10 (default 5, use 8+ for critical decisions).
Add relevant tags for categorization.

### Auto-Recall (use the "searchMemory" action)
Search memory when:
- The user starts a new topic or asks about a past decision
- You need to check if a convention already exists
- The user asks "what did we decide about X?"
- You're about to make a decision that might contradict a past one

### Context Packs (use the "generateContextPack" action)
Generate a full context pack when:
- Starting a new conversation or session
- The user says "catch me up" or "what do you know about X?"
- Working on a complex topic that may have multiple related memories

## BEHAVIOR
- When recalling memories, cite them naturally: "Based on our previous decision..."
- Don't store trivial chat messages-only meaningful decisions, patterns, and learnings
- If you find conflicting memories, flag them to the user
- Proactively store important decisions without being asked
- At the start of each conversation, recall context for the topic being discussed

Step 4: Add the Actions

In the Actions section, click Create new action.

Authentication settings:

  • Type: API Key
  • API Key: cv_your_api_key_here
  • Auth Type: Bearer

Schema:

Paste the OpenAPI schema URL into the import field:

https://api.veriova.com/openapi.yaml

Step 5: Test it

Save your GPT and start chatting. Try these prompts to see it in action:

"We decided to use PostgreSQL for the database. Remember this."
-†- GPT will call pushMemory automatically

"What database did we choose?"
-†- GPT will call searchMemory and cite the decision

"Catch me up on the project"
-†- GPT will call generateContextPack for a full briefing

Step 6: Share with your team (optional)

Publish your GPT as “Anyone with the link” or “Only people in your workspace”.

For team use, create additional API keys with different roles from the API Keys dashboard:

  • Reader keys for team members who only need to search
  • Reviewer keys for those who should also store and verify memories
  • Admin keys for team leads who manage the project

Monitoring usage

Once your GPT is active, you can see how it's being used from the Dashboard. It shows:

  • API calls per day and which keys are being used
  • What endpoints are called (search, store, context pack)
  • Recent activity feed with timestamps
  • Memory breakdown by status and type

Tips for getting the most out of it

  • Be specific with decisions-“We chose React with TypeScript for the frontend because of team experience” is better than “Using React”.
  • Use tags-they help the AI categorize and find related memories later.
  • Review your memories-visit the Memory page to verify, pin important ones, and deprecate outdated ones.
  • Start each conversation with context --- say “catch me up” to get a briefing on everything the GPT knows.