Govern, build, scale.

From app to hardware, deployed anywhere. The gofl platform enables IT teams to safely put agents in production.

App layer
Build with anything
BuilderLangGraph LangGraphCrewAI CrewAIGoogle ADK CLI / SDK
governed
Control plane
Agent Gateway
Identity Policy Audit
one contract
Model layer
Self-hosted or any provider
InferenceOpenAI OpenAIAnthropic AnthropicGemini GeminiBedrock BedrockVertexAI Vertex AI Self-hosted
Enterprise-grade governance

Govern every call

Every model, tool, MCP and database call passes one gateway — under one identity, one audit trail, one policy. Same governance, builder-built or your own code.

Sources · clients
CLI / IDE
AI agents
Apps & clients
Agent gateway · control plane
Agent Gateway
Identity & RBAC
Policy & guardrails
Secret injection
Rate limits & budgets
Routing & failover
Audit & tracing
Destinations · models & tools
ModelsOpenAIAnthropicGemini
MCP serversGithubNotion
DatabasesSnowflake
APIs / services
OTel collector
stream to your SIEM
Datadog Elastic Grafana+ your SIEM

Secrets never reach the model

The gateway injects a scoped, short-lived credential at egress. The agent and the LLM never see a standing secret.

Every call attributed

Bound to the signed-in person or a named service account — human or machine. Attributed, never NULL.

One audit trail

Model spend and every tool, MCP and database call in a turn share one trace under one identity.

Govern your own code

Declare models, tools and access as Kubernetes resources. Your engineers’ own agents get the same plane — as code.

Open by design

Keep your way of working, and models

gofl is an open seam, not a walled garden. Keep the agent framework your team already uses, and run whatever model fits the job — governed the same either way.

Connect in one line

The gateway speaks the OpenAI API — point your framework at it and every call runs under the same identity, policy and audit. Pick yours:

agent.py
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
 
llm = ChatOpenAI(
model="qwen3-32b",
base_url="https://gofl.acme.com/v1", # ← gofl gateway
api_key=workload_token,
)
agent = create_react_agent(llm, tools)

Any model, any provider

Open-weight models on your own GPUs, or a frontier model reached through the provider you already run. One contract for all of them — swap the model, not your code.

Gemini
Mistral
OpenAI
Meta
Anthropic
DeepSeek
Reached through
Bedrock BedrockVertexAI Vertex AIAzureAI AzureGroq Groqtogether.ai Togetherself-hosted vLLM
Usage & adoption

Track adoption and spend

One organisation-wide view of every agent, token and dollar — see what your teams are adopting, where the spend goes, and stay inside budget.

Analytics

Organization-wide AI usage, spend, and model adoption.

Agents
14
9 deployed
+3 vs last month
Tokens
5.3M
4.2M in · 1.1M out
+24% vs last month
Spend
$312
+17% vs last month
Budget used
66%
5.3M / 8.0M tokens
Set budget

Token usage · monthly

input output
01.5M3.0M4.5M6.0MJanFebMarAprMayJun

Monthly budget

5.3M/ 8.0M tokens
66% used$312 cost
One platform, many agents

Ship agents and workflows with gofl’s builder

Press deploy and every agent is automatically governed — identity, policy and audit, out of the box.

Input
AzureOutlook

New ticket from the support inbox

Azure ticket_8413
Agent
support-triage

Classify severity and route to the right team

prompt

Read the ticket, set priority and pick the owning team.

Anthropic Claude Sonnet 4.6· 382 tokens
Action
Assign ticket

Route via ServiceNow as the signed-in agent

servicenow
support-triage · Claude Sonnet 4.6

Triage and route every ticket

Classify severity, pick the team and assign the owner — acting as the signed-in agent, every step on the audit trail.

Build this for your team
  • Severity + team in one pass
  • Routes as the signed-in identity
  • SLA timer started, logged
Deploy anywhere

Deploy where you are comfortable

Self-host on the infrastructure you already run, or let us run it for you — the same platform and the same governance, either way.

gofl installs as an appliance on the infrastructure you already run — any cloud, your own Kubernetes, bare metal, even air-gapped. Nothing phones home. One helm install, one knob: a domain.

terminal
$ helm install gofl gofl/gofl \
      --set domain=gofl.acme.com
Runs onsame appliance, everywhere
AWSAWS
AzureAzure
GoogleCloudGoogle Cloud
Kubernetes
OpenShift
Bare metal
On-prem
Air-gapped

Book a demo.

Tell us what you want to build and we’ll get back to you.

Or email me directly — [email protected]

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