Not just another AI tool.
Engineered for absolute grounding.
Most AI platforms are thin wrappers around commercial APIs that guess when they don't know. Bweb Agents is built on an isolated, multi-tier control plane designed for factual grounding, sandboxed execution, and audited promotion.
Four foundational pillars of control.
Every layer—from data ingestion and retrieval to LLM completion and tool approvals—is enforced with strict verification boundaries.
Enforced Citation Grounding
Our private runtime requires every factual claim to cite exact chunk IDs from your indexed knowledge. If your documentation doesn't have the answer, the agent explicitly abstains instead of fabricating plausible fiction.
- Strict JSON response schema with source citation validation
- Graceful abstention on unsupported facts or missing context
- Untrusted input fencing prevents prompt injection attacks
Dual-Environment Isolation
Each organization receives completely separate databases, queues, and vector spaces for Sandbox and Production. Test new prompt versions and ingest experimental data without risking live customer interactions.
- Isolated PostgreSQL databases and BullMQ queues per tenant
- Dedicated subdomains:
org.bwebagents.com&org.sandbox... - Shared wallet attribution prevents sandbox resource abuse
Audited & Hashed Promotion
Moving from Sandbox to Production is never an unverified mirror. It is an explicit, two-phase review with canonical review hashes, automated credential sanitization, and mandatory regression evaluation passes.
- Cryptographic review hash guarantees promotion integrity
- API keys and secrets are never copied across boundaries
- Immutable version snapshots require passing regression tests
Human-in-the-Loop Action Approval (Proposal-Only)
Agents on Bweb Agents cannot autonomously trigger database writes, send unreviewed messages, or execute destructive tool actions. When an agent identifies a task, it emits a structured action proposal with arguments and reasoning. Execution requires explicit owner approval.
Why architecture matters.
See how the Bweb Agents enterprise control plane compares to off-the-shelf chatbot builders.
| Capability | Generic AI Wrappers | Bweb Agents Platform |
|---|---|---|
| Grounding & Citations | Bypassable Model decides whether to cite; hallucinations frequent when context is missing. | Enforced In Runtime Stateless runtime validates source chunk IDs; non-cited claims trigger immediate abstention. |
| Environment Isolation | Single Environment Edits directly modify live production agents or rely on shared single-table tenancy. | True Sandbox → Prod Dedicated databases, queues, and vector indices for sandbox and production per client. |
| Release Promotion | Instant Sync No verification gate; untested prompt edits go immediately live to end users. | Cryptographic Review Two-phase transfer review, immutable release snapshots, and mandatory regression tests. |
| Tool & Action Safety | Autonomous Webhooks Agent triggers external APIs directly, creating security and data-loss risks. | Proposal-Only with Approvals Agent can only propose actions with arguments; human owner approval is required to execute. |
| Infrastructure & Security | Shared Multi-Tenant Cluster Single host failure or noisy neighbor impacts all customers. Plaintext backups. | Multi-Tier VPS + Cloudflare Control plane separate from tenant execution; AES-256-GCM encrypted database checkpoints. |
Isolated hosting tiers.
Public traffic and billing are physically segregated from client workspaces, data queues, and LLM runtimes.
bwebagents.com (Marketing & Docs)•
/account (Billing, Stripe webhooks, Passkeys)• Organization credit wallet & reservation ledger
• Central control database (PostgreSQL)
• AES-256 encrypted checkpoint generation
app.bwebagents.com & tenant subdomains• Separate Production & Sandbox databases
• BullMQ ingestion worker & pgvector indexing
• Private Python grounded runtime (8100)
• Loopback-only service binding; zero public DB ports
Put your knowledge to work.
Start with one use case. Build the right agents around it.
Build your agent team Talk through your use case ↗