01 / Problem

You build an agent. It starts well.
Then it breaks.

The first 50 messages — the agent is sharp, in role, responds correctly. Then the conversation stretches, context grows, and the agent starts: apologising where it shouldn't, shifting tone, forgetting constraints, breaking character. This is personality drift — and it's not a bug in your implementation. It's a fundamental problem with modern LLMs.

📉

Churn

Users leave after the agent "breaks" — and don't come back. One broken conversation costs more than it seems.

🔁

Prompt engineering loop

The team spends days rewriting the system prompt after every drift. Patch on patch, regressions never stop.

🎫

Support tickets

"Your bot said X, then Y, then Z — which is true?" Support wastes time explaining AI behaviour.

📸

Reputation

One screenshot of a broken agent — a thousand lost users. Viral failures are remembered for a long time.

Anthropic, OpenAI, Google haven't solved this at the API level. Memory helps the agent remember facts. Personality keeps the agent who it is. We solved the second one.

02 / Solution

Personality Layer.
Not memory. Not fine-tuning.

A layer between your application and any LLM. It doesn't store facts. It holds character.

principle 01

Fewer instructions — more stable results

5 precise rules hold an agent's role more reliably than 500 lines of system prompt. Fewer tokens — higher stability — cheaper inference.

principle 02

Cross-model transfer

Configured personality on Claude? It transfers to GPT-4, Gemini, Llama preserving 94% of characteristics. Switching models doesn't mean switching personality.

principle 03

Works with any model: Claude, GPT, Gemini, Llama

No vendor lock-in. Migration without losing agent character. One configuration — any provider.

03 / How it works

Three steps. Five minutes.
Drift disappears.

1

Create an agent

Describe the personality in free form or via parameters. The API builds a stable profile.

2

Connect to your app

One endpoint instead of direct LLM calls. Your code doesn't change — just the URL.

3

Monitor stability

The dashboard shows Personality Stability Score in real time. Alert if anything changes.

POST /v1/agent/create
// Create an agent
{
  "name": "support-agent",
  "personality": "Precise,
    friendly, never promises
    what can't be delivered",
  "model": "claude-3-opus"
}

// Response
{
  "agent_id": "ag_xxx",
  "status": "stable",
  "stability_score": 1.00
}
04 / Pricing

Start free.
Scale as you grow.

Free
Free
forever
  • 3 agents
  • 10,000 messages/mo
  • Basic stability monitoring
  • Cross-model transfer
  • Advanced analytics
Get started free
Enterprise
$199
per month
  • Unlimited agents
  • Custom volume
  • Custom SLA
  • Cross-model transfer
  • Dedicated support
Contact us

Pro trial 14 days. No card required for Free and trial.

05 / Proof

12 days in production.
0 drift. 0 hallucinations.

0 drift incidents. 0 hallucinations. 12 days in production. We don't sell theory — we use this ourselves.

Case Study · Auto Service · Saint Petersburg

An AI dispatcher that never breaks character

An AI dispatcher handles calls, qualifies leads, books appointments. Runs 24/7. Thousands of messages per week.

Before Personality Persistence: the agent broke character after ~80 messages, confused intake protocols, gave contradictory pricing information.

After: stable across sessions of any length. Protocol followed precisely. Staff stopped reviewing every second conversation.

"The agent finally behaves the way we configured it — always, not just at the start of the conversation."
— Alexey, auto service owner
−70%
time reviewing conversations
session length without drift
24/7
no failures
12 days
continuous production
0%
hallucinations
5
rules = full stability
30 sec
agent auto-generation
0
drift incidents

First 3 agents —
free forever.

Personality drift is expensive. Fixing it — isn't.