EXtremely Integrated Layers for Enterprise Development of AI
Agent‑First • Python‑Unified • Zero GlueThe unified Python framework for building trustworthy, high-performance agentic applications — streaming, tools, memory, and UI included. Ship faster with less code.
Layering frameworks often leads to bloated, hard-to-maintain, brittle Apps. Exiled.AI replaces the patchwork with a cohesive high-performance stack.
Natively integrated components and key value drivers.
Native agents, models, tools, memory & workflows minimize overhead.
Optimized for low‑latency SSE & high‑concurrency agent communication.
Fast server‑rendered components with smart layout defaults.
Zero‑dependency validation & transformation. Enables <1ms cold starts & streaming.
Specifically designed for building high-performance, controllable AI agents. Native workflows, memory, tools, and streaming reduce boilerplate, enabling faster iteration on core agent logic.
One language (Python), one mental model across the entire stack. **No Dependency Hell:** Avoid version conflicts and spend time coding, not troubleshooting. Our tiny (<5k LOC), stable foundation enables rapid "vibe-coding" and iteration.
Escape rigid frameworks. Exiled.AI provides flexible building blocks with full control, allowing you to tailor models, tools, UI themes, security, and components precisely to your unique application needs.
demo_fred.pyThis runnable app connects all pillars. An Agent with tools connects seamlessly to the UI. No glue code required.
from __future__ import annotations
from app import App
from components import Card, Div, H1, P
from components_agent import AgentChat
from tools_fred import fred_csv, fred_search
from workflow import Flow, agent, define_agent
AGENT_ID_FRED = "FRED"
@Flow(AGENT_ID_FRED) # Define the workflow
def fred_flow():
instructions = "You are a friendly expert..."
agent(define_agent( # Define the agent
name="FREDAgent", model="gpt-5-nano",
instructions=instructions, tools=[fred_search, fred_csv]
))
app = App(title="FRED Data", theme="dark") # Define the App
@app.page(id=AGENT_ID_FRED, is_default=True) # Define UI page
def fred_ui():
return Div( # Build UI w/ Python
Card(H1("📈 FRED Assistant")),
AgentChat(agent_name=AGENT_ID_FRED, show_logs=True)
)
# app.run() - That's it!Build complex agent interactions and manage data flow using native, high-performance Flows.
DataFrame acts as both a **Validator** for AI outputs and a **View-Model** for UI presentation, eliminating glue code.
// Schema defines the contract
schema = Schema([...])
try: // Validate LLM output
df = DataFrame.from_rows(
llm_output
).with_schema(schema)
except SchemaError as e:
handle_error(e)// Schema has types + formatters
schema = Schema([...])
df = DataFrame.from_rows(
data
).with_schema(schema)
// Sort on logical type
df_sorted = df.sort_values(...)
// Format for UI on export
payload = df_sorted.to_table(
render=True
)Align with global AI frameworks through built-in transparency and control.
Exiled.AI helps firms align with global AI governance frameworks by providing one unified stack where every component—server, UI, agent, and data—runs under the same security and control boundary. In regulated environments, control is everything. It’s far easier to demonstrate oversight, access management, and change control when you operate a single, auditable system without hidden third-party dependencies or opaque microservices.
Our Tree Logs and Artifacts create an end-to-end Audit Trail that captures each agent’s inputs, reasoning steps, tool invocations, and outputs. This traceability supports EU AI Act transparency and NIST AI RMF explainability requirements, while also meeting the expectations of financial regulators (SEC, FINRA, FCA, PRA) for model risk documentation and supervisory review. Compliance teams can literally replay an AI decision — seeing what the agent knew, did, and produced.
Because workflows, data handling (via Data Governance schemas), and user controls are all native and deterministic, evidence of governance is built in. The system enforces predictable behavior, making it straightforward to embed Human-in-the-loop checks. Privacy and data retention policies flow through the same stack, simplifying GDPR/CCPA obligations.
Operationally, a unified framework reduces vendor sprawl, accelerates risk assessments, and streamlines validation. Compliance reporting becomes faster and more credible with logs, artifacts, and configurations available through one consistent schema. This consolidation shortens audit cycles and lowers the total cost of governance.
Ultimately, Exiled.AI turns regulatory alignment into a design advantage through built-in transparency, predictable workflows, and explicit Control points—allowing confident innovation.
Exiled.AI is preparing for launch. Stay tuned for updates on how to get started building the next generation of trustworthy agentic applications.