From discovery to live production in 30 days.

A five-phase delivery blueprint backed by dedicated solution architects, custom MCP integrations, and strict SLAs — or join the team building it.

Request an Enterprise AI Audit Apply — Engineering Tracks

The 5-Phase Delivery Blueprint

Predictable from audit to go-live.

Days 1–5

Operational Audit & Solution Architecture

Process mapping, bottleneck analysis, Agent Builder tool definition, and ROI business case validation.

Days 6–10

Governance & Security Accord

Zero-trust boundary definition, PII redaction rules setup, AI Governance guardrail configuration, and custom MCP schema design.

Days 11–20

Production Pilot & Agent Training

Rapid deployment of autonomous agents into sandboxed test environments with live simulation tracking and token optimization.

Days 21–30

Full Enterprise Scale

Go-live production launch, integration with core ERP/CRM/Core Banking backends, and operational team enablement.

Ongoing Lifecycle

Dedicated Solutions Architect

Continuous prompt tuning, MLOps model drift tracking, continuous feature updates, and 99.9% SLA enforcement.

Active Engineering Tracks

Build the runtime other teams trust.

Active Tracks

agent-builder-runtime.ts governance-proxy.py fintech-settlement-engine.py voice-agent-runtime.ts mcp-tool-bindings.ts

1import {{ AgentBuilder }} from "@risingpoint/core";
2
3const agent = new AgentBuilder({{
4  tools: mcp("underwriting", "pricing", "compliance"),
5  governance: {{ redactPII: true, proxyMs: 5 }},
6  policy: {{ retention: "zero", region: "sovereign" }},
7}});
8
9await agent.deploy({{
10  workflow: "policy-origination",
11  sla: {{ uptime: 99.9, latencyMs: 2000 }},
12}}); // immutable audit trail on every tool invocation

➪ BUILD: SUCCESSFUL (100% TESTS PASSED — 99.9% SLA VERIFIED)

Architects wanted.

Distributed Python/TypeScript runtime engineers, fintech settlement specialists and AI governance architects — talk to us.

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