works with your stack
Drop-in SDKs and APIs that meet your runtime where it lives.
newNew: enterprise guardrail blueprints + SOC 2 toolkit
enterprise ai agent control plane
proompteng lets platform and security teams govern, secure, and scale AI agents across any cloud with policy-as-code guardrails, unified observability, and multi-model orchestration.
soc 2 evidence • deploy in your vpc • open-source control plane
- compliance-grade guardrails
- Enforce policies from GitHub, sign every action, and ship audit-ready evidence.
- multi-model orchestration
- Route across OpenAI, Claude, Gemini, DeepSeek, and on-prem weights with one API.
- traceable decisions
- Replay conversations, diff agent runs, and share post-mortems in minutes.
control plane fundamentals
What is an AI Agent Control Plane?
An AI agent control plane is the governance and orchestration layer that connects models, tools, and data while enforcing policy, observability, and deployment guardrails. proompteng centralizes these capabilities so platform, security, and operations teams can launch agents with confidence across clouds.
- Policy-as-code governance
- Enforce prompts, tools, and data access through versioned policies, approvals, and SOC 2-ready evidence.
- Unified observability
- Capture traces, replay agent runs, and monitor quality, cost, and latency in a single pane of glass.
- Multi-model routing
- Route across OpenAI, Claude 3.5, Gemini 2.0, DeepSeek, and self-hosted weights with policy-aware fallbacks.
- Operations automation
- Automate playbooks for rollouts, incident response, and post-mortems while keeping stakeholders in the loop.
How proompteng compares to Agentforce and Gemini
| Capability | proompteng | Agentforce 360 | Google Gemini for Agents |
|---|---|---|---|
| Policy-as-code guardrails | Versioned policies, approvals, and automated SOC 2 mappings out-of-the-box. | Limited to Salesforce ecosystem guardrails; custom code for external tools. | No native policy engine; relies on Cloud IAM and custom middleware. |
| Multi-model orchestration | Abstracted routing for OpenAI, Claude, Gemini, DeepSeek, open weights, and custom adapters. | Optimized for Einstein/GPT; external models via integrations with added latency. | Vendor-locked to Gemini family; third-party weights require Vertex custom pipelines. |
| Observability & replay | Full trace capture, diff tooling, eval hooks, and incident post-mortem exports. | Basic monitoring dashboards; limited replay for non-Salesforce channels. | Logging via Cloud Logging; replay needs custom instrumentation. |
| Deployment flexibility | SaaS or self-hosted in your VPC/Kubernetes with Terraform + Argo CD automation. | Runs in Salesforce cloud; no self-hosted option. | Runs on Google Cloud; hybrid requires complex networking. |
Looking for a deep dive? Request the governance checklist to benchmark policies, observability, and deployment flexibility across platforms.
trusted by launch partners
Designed with teams operating regulated workloads
From biotech to fintech, proompteng keeps governance and velocity in the same workflow.
Northwind Research
governed AI agents for biotech
Lambda Logistics
dispatch automation across 18 markets
Atlas Legal
document AI agents with audit trails
Helios Cloud
multi‑model experimentation at scale
Orbit Studio
creative tooling for product designers
Mosaic Analytics
regulated AI agents for fintech
outcomes that stick
ship faster, govern better, spend less
Every launch partner sees measurable wins within the first week of adopting proompteng.
- faster governance sign-off
- 40%
- lower runtime spend
- 45%
- observed uptime
- 99.9%
Policy-as-code reviews and SOC 2 evidence bundles cut approval cycles nearly in half.
Multi-model routing and caching trim wasted LLM calls without sacrificing quality.
Multi-region control plane with progressive delivery and instant rollback.
platform pillars
why teams choose proompteng
As devtools infrastructure for AI agents, the control plane stitches every capability together. Every pillar ships with secure defaults, deep observability, and zero vendor lock‑in.
run anywhere
Deploy on any cloud or on-prem with policy-controlled rollouts.
built‑in visibility
Traces, evals, and cost metrics baked in from the first run.
model choice
swap providers and embeddings without lock‑in.
guardrails
rate limits, safety checks, and audit trails by default.
memory + rag
pluggable stores for short/long‑term memory and retrieval.
control plane
Govern agents with policy-first workflows
Version policies in git, roll out changes safely, and orchestrate routing, memory, and tools across every environment.
control plane
tools, routing, memory, and policies across environments.
scale + govern
autoscale with retries; emit traces and cost metrics.
sdk + apis
http and adapters to integrate with any app or workflow.
connect anything
Drop-in integrations for models, stores, and workflows
Adapters for the providers and data sources you already use — no vendor lock-in, no brittle glue code.
vector + storage
milvus, object storage, and search connectors.
frameworks
vercel ai sdk, langgraph, langchain, llamaindex, autogen, crewai.
providers
openai, gemini, azure, and oss via adapters.
self-hosted weights
llama 3.1 405b, mistral large, qwen2, nemotron via on-prem deploys.
domain copilots
financial, legal, healthcare tuned models with policy enforcement.
trust at scale
Secure, observable, human-in-the-loop by default
Guardrails, audit trails, and evaluation pipelines keep every AI agent compliant and reliable from day one.
secrets isolation
scoped tokens and rbac for model/tool usage.
audit trails
every call and data access is logged.
pii handling
field‑level encryption and redact‑on‑read policies.
tracing
opentelemetry‑backed traces and dashboards.
evals + guardrails
ci gates, safety checks, cost controls.
enterprise ai agent use cases
regulated industries
launch compliant customer support and underwriting copilots with SOC 2 evidence and guardrails.
operations automation
coordinate agent swarms for logistics, field service, and supply chain handoffs with audit-ready playbooks.
agent observability
trace, replay, and evaluate AI assistant decisions to improve win rates and reduce hallucinations.
self-hosted agents
ship on-prem orchestration for sensitive data using mistral, gemini, and llama weights in your VPC.
multi-model routing
route across o1, claude 3.5, deepseek r1, and internal fine-tunes with policy-aware fallbacks.
governed rag
connect retrieval layers to agent memory with approvals, retention policies, and audit trails.
model catalog
openai o1-preview
reasoning-grade model with native tool use and long context support.
claude 3.5 sonnet
balanced flagship with 200k context and audit-ready compliance scores.
deepseek r1
open reasoning weights optimized for complex workflows and cost efficiency.
gemini 2.0 flash
multimodal stack for real-time agents with streaming outputs.
llama 3.1 70b
self-hostable model with tuned guardrails and policy routing support.
voyage multipass
high-signal embeddings and rerankers for hybrid rag pipelines.
launch playbook
From prototype to governed production in one week
Drop in proompteng where it fits today — then scale to full governance without rearchitecting.
~90 minutes
day 0: connect your stack
Drop in the SDK, sync schemas, and register tools without rewrites.
outcome: AI agents running in staging with policy packs applied.
~half day
day 1: instrument everything
Enable OpenTelemetry export, start collecting traces, and stand up eval suites.
outcome: Dashboards streaming cost, latency, and win/loss scores.
~one day
day 3: go live safely
Progressive rollouts, automated guardrails, and human-in-the-loop overrides.
outcome: Production traffic with controlled exposure and auto rollbacks.
continuous
day 7: scale globally
Promote playbooks to new regions, replicate memory stores, and reuse workflows.
outcome: Multi-region availability with shared governance and routing.
customer spotlight
proompteng turned weeks of glue work into a one‑day launch for our first AI agent — with end‑to‑end governance ready for audit.
Head of Platform · Design Partner Co.
questions
AI agent governance FAQs
Still unsure? Reach out for a guided walkthrough tailored to your compliance posture, deployment model, and policy requirements.
ready to launch
Operate every AI agent with production confidence
Deploy to your cloud, keep the governance you need, and keep iterating with the tools you love.
soc 2 evidence • deploy in your vpc • open-source control plane