Trust your AI’s answers.

Conflict-aware memory that detects, resolves, and audits knowledge
– so your agents stay consistent and your reviews pass fast.

BYO models & storage
VPC/on-prem option
Decision ledger export
Brain by The Up - Pipeline
Problem

The real reasons AI projects slip

LLMs are fine; your memory isn’t governed. Contradictions slip in, you don’t see them, and the sprint burns.

Contradictions reach prod

Same question, different answers; reviewers reopen tickets.

No quick way to fix

Engineers burn cycles rebuilding prompts not resolving the conflict.

Trust collapses

PMs stop shipping agent features; pilots stall.

↓ re-checks per answer · ↑ first-pass accept rate
Storage ≠ governance. Vector/graph DBs don’t detect contradictions or record human approvals.
How It Works

Catch, route, fix – inside your workflow

Catch conflicts, resolve with approvals, and prove every answer with a decision history.

Detect at source

Brain cross-check what agents ingest/fetch and flag conflicts in real time (runs, RAG fetch, sync).

Route to the right person

Slack/Teams alerts with context; click opens the Resolve panel or approve inline; creating dynamic AI-ready SSOT.

Apply & remember

Decision updates the governed memory; agents stop disagreeing; ledger updates automatically.

No migration—keep vectors/graph; we add governance via events & webhooks.
Features

Build for builders and reviewers

Integrate fast, keep your stack, and resolve conflicts without leaving your flow.

pip install theup-sdk
from theup import Brain
brain = Brain(store="neo4j")
agent = brain.wrap(my_agent)
conflicts = agent.detect_conflicts()
agent.resolve(conflicts).export_ledger("csv")
Developers

Drop-in governance. Zero migrations.

✔  10-minute SDK (LangChain/LangGraph ready).
✔  Keep your stores (Neo4j/Pinecone/LanceDB).
✔  Events & webhooks (subscribe to conflicts; embed Resolve in your app).

Compliance & Ops

Approvals, evidence, and time-travel answers

✔  Approve in Slack/Teams or in the panel.
✔  Time-travel answers (see what the AI “knew” on any date).
✔  One-click exports for aditors (CSV/PDF).

Why Us

Storage ≠ governance

Vector search fabricates facts. Auto-generated knowledge graphs contradict themselves. Brain flags every conflict and locks the truth—no Cypher skills required, we cut errors to 8% (synthetic benchmark on 1 k pharma SOP docs; methodology on request).

Chart showing benchmark data with VectorRAG 35 %, GraphRAG 18 %, Brain 8 % error/hallucination rates

Use Cases

Where Flat AI Fails
Brain works in symbiosis with SMEs in Your team, so you can apply it in high-stake situations where other Agentic AI architectures fails.

Regulatory Q&A

Cited answers with version history & conflict notes.

Industries:
• Pharma (GxP, EMA)
• Energy (CSRD, CBAM)
• Finance (MiFID II, SFDR)
Decision Support

Query historic decisions and playbooks in seconds - no more Slack archaeology.

Functions:
• Sales (playbooks, lost deals)
• Product (feature decisions)
Exception Handling

Every override gets a reason chain. Perfect for audits, crucial for trust.

Domains:
• Finance (KYC, compliance flags)
• Insurance (claims deviation, fraud)
Incident R-C Analysis

Logs → causal chain → root fix, not symptom patch.

• R&D (experiment troubleshooting)
• Manufacturing (process deviation)
✔ Pilots active in regulated sectors   ✔ EU based GDPR-aligned   ✔ SOC 2 program underway   ✔ VPC/on-prem deployment

Avoid the next rollback

See how Brain stops contradictions before they derail the sprint.

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