Audit logs, PII redaction, OAuth isolation, MCP hosting, and chat-platform deployment — all built in. No containers to maintain, no secrets to rotate, no safety stack to build.
Six capabilities your security team will actually ask about. All built in. All on every plan.
Three-stage pipeline: heuristic → LLM guardrail + URL safety in parallel → block or rewrite. Catches prompt injection, unsafe URLs, and policy violations before tools execute.
Every untrusted tool result passes through a PII scan. Emails, SSNs, phone numbers, and addresses get redacted with placeholders. Never blocked. Always logged.
Read/write permissions per tool, per integration. When write is disabled, the LLM literally cannot see write actions. Least privilege by construction, not by policy.
OAuth tokens never reach the LLM. The tool executor injects credentials server-side at the moment of use. The agent never sees a secret.
Every tool call, every guardrail event, every safety scan logged with tenant and user attribution. Replayable, filterable, exportable.
Operational discipline shaped by U.S. military experience. Production AI runs like a well-managed NOC, not a playground.
One agent, one safety stack, one audit log — surfaced across every chat platform your team uses. OAuth handled. Slash commands included.
Both work. They serve different teams.
| Capability | Self-Hosted Agent Stack | Tech Ringer AI Hosted Agents |
|---|---|---|
| Runtime setup | Containers, workers, browser sessions, updates | Hosted runtime, managed |
| Secrets | User stores and rotates credentials | Centralized OAuth + isolated from LLM |
| Guardrails | User implements safety layers | Input + URL + tool-result, built in |
| PII handling | User builds redaction | Native PII redaction on every result |
| Audit logs | User builds logging + retention | Default, per-tenant, per-user |
| Tool access | User wires APIs + MCP servers | Managed MCP + unified tool abstraction |
| Chat deployment | Per-platform integration work | 8+ platforms supported out of the box |
| Best fit | Teams with engineering capacity wanting full control | Teams that want agent outcomes without infrastructure burden |
Natural-language workflows that route tickets, summarize PRs, post to channels, and update records — with capability gates on every step.
Connect your team's tools via the Model Context Protocol. Capability badges (read/write) per tool. Discoverable. Auditable.
On-call summarization, deploy status agents, incident triage helpers — operating inside your audit boundary, not outside it.
Multi-tenant org switching, role-based access (owner/admin/member/viewer), and external user identity mapping for chat-platform users.
Yes — that's the design goal. We publish our posture at /security: AES-256-GCM encryption at rest, OAuth credentials isolated from the LLM, HMAC SHA-256 service-to-service authentication, per-tool capability gating, and audit logs by default. Most security teams find a 30-minute review covers what they need to approve a pilot.
Every agent action — tool calls, guardrail events, PII redactions, capability checks — is logged with tenant and user attribution. Audit logs are filterable in the dashboard, exportable for compliance review, and replayable so a reviewer can reconstruct exactly what the agent did and why.
Yes. Capability gating works at the tool-instance level — read and write permissions are independent toggles. When a write capability is disabled, the LLM literally cannot see the write actions in its tool list. Least privilege is enforced by construction, not by policy that depends on the model behaving.
OAuth tokens and API keys never enter the LLM context. They live in an isolated tool executor that injects them server-side at the moment of tool invocation. The agent cannot exfiltrate a secret because it never sees one. Secrets are encrypted at rest with AES-256-GCM using versioned key rotation.
No. We do not train models on customer conversations, files, or any other tenant data. PII is redacted before any tool result is sent to a third-party LLM provider, so the upstream models don't see your sensitive data either.
Slack, Microsoft Teams, Discord, Google Chat, Telegram, WhatsApp Business, SMS (via Twilio), and in-app messaging. All deployments share the same safety stack and audit log — adding a new platform doesn't expand your security surface area meaningfully.
No engineering lift. No multi-quarter integration project. Just a team account, your tools connected, and the audit log waiting.