Real-Time Multi-Agent Intelligence Infrastructure for Voice AI

The Intelligence Behind Every AI Conversation.

Real-Time Multi-Agent Intelligence Infrastructure for Voice AI

ANDIP LIVE is developing a real-time intelligence layer that enables conversational AI agents to request parallel research, retrieve verified business context, and receive policy-aware recommendations while conversations remain active.

Development Status
Architecture and Early Engineering
Community Alpha
Q1 2027
Target Launch
Q2 2027
ANDIP LIVE hero diagram: one customer speaking to a primary voice agent, supported by the Live Decision Broker and coordinated specialist intelligence A customer connects to a primary voice agent. The voice agent connects to the ALI Live Decision Broker. The broker coordinates four supporting intelligence domains: market, operations, policy, and evidence. The voice provider keeps the conversation while ANDIP LIVE supplies structured intelligence and recommendations. ONE VOICE COORDINATED SUPPORT ANDIP LIVE INTELLIGENCE CUSTOMER Live call PRIMARY VOICE AGENT ALI LIVE DECISION BROKER MARKET External verification OPERATIONS Inventory and systems POLICY Allowed actions EVIDENCE Sources and confidence

Conceptual system diagram. Motion is optional and respects reduced-motion preferences.

01 — The Problem

AI can speak. But can it make an informed decision in real time?

Fluent conversation does not guarantee reliable coordination across changing business data, external evidence, and authorization rules.

Voice agents can answer calls, qualify inquiries, schedule appointments, and hold natural conversations. But the ability to speak fluently is not the same as the ability to make informed business decisions.

A voice agent may know a product catalog, pricing policies, and frequently asked questions. The difficulty appears when a customer introduces something unexpected — a competing price, a new promotion, an alternative itinerary, or an offer that was never part of the original conversation script.

Answering accurately can require consulting several external sources and completing multiple specialized tasks. A voice agent cannot afford to fall silent for an extended period while a customer waits on the telephone. That is the infrastructure gap ANDIP LIVE is designed to address.

The infrastructure gap Coordinate several time-bounded lookups and return a useful answer without forcing the caller to wait for a full background workflow.
Illustrative scenario

A customer challenges the price

“Why is your room $130 when another site shows $100?”

The comparison may involve different dates, room types, taxes, cancellation terms, or availability. Four questions must be resolved while the call stays live:

  • Competitor rate — same dates and conditions?
  • Inventory — available now?
  • Pricing policy — what can be offered?
  • Customer context — what is relevant here?

Figures shown are illustrative examples used to describe the workflow. They are not real competitor prices or performance results.

02 — The Approach

Supporting intelligence without interrupting the conversation

Instead of replacing existing voice platforms, ANDIP LIVE operates as an intelligence and decision-support layer connected to them.

The primary voice agent remains responsible for listening, speaking, understanding the customer's request, and maintaining a natural conversation. Behind the scenes, ANDIP LIVE can activate specialized supporting agents to retrieve information, investigate market conditions, verify claims, calculate available offers, assess business rules, and return actionable context to the conversational agent.

These supporting agents are not independent customer-facing voices. They are an invisible workforce coordinated to help the primary agent respond accurately and efficiently.

Provider-neutral by design

Designed to support multiple conversational AI providers and runtime technologies through a common integration interface.

Recommendation is not permission

Proposed commercial actions remain subject to applicable business authority and eligibility rules.

Every element described on this website is proposed or under development unless stated otherwise. ANDIP LIVE is not a released commercial product.

Request and response path

Conceptual

Conceptual request and response path between a voice agent and supporting intelligence The primary voice agent submits a structured request with context, deadline and permissions. ANDIP LIVE classifies the request, executes bounded work, verifies evidence and applies policy, then returns incremental updates and a permitted recommendation. PRIMARY VOICE AGENT Submits request · context · deadline · permitted actions LIVE DECISION BROKER Classify · plan · bound · prioritize · route BOUNDED WORK Lookups · API calls · agent tasks EVIDENCE + POLICY Verify · rank · authorize INCREMENTAL UPDATE TO THE AGENT First useful evidence now · more detail as it arrives

Design principle: return useful, qualified information as it becomes available. Do not wait for every background task.

03 — Two Intelligence Modes

Prepared knowledge meets on-demand research

Prepared knowledge handles predictable questions. Live work resolves the exception.

Mode A

Background Intelligence

Refresh approved data before calls begin

  1. Business policies and offer rules
  2. Product, inventory, and pricing snapshots
  3. Approved competitor observations
  4. Time stamps, sources, and expiry rules

Creates a time-stamped knowledge layer that conversational agents can consult quickly, without a live deadline.

Mode B

Live Intelligence

Investigate only what the current call needs

  1. Targeted external verification
  2. Current operational system lookup
  3. Parallel specialist comparisons
  4. Deadline-aware partial results

Tasks operate under strict time limits and return partial results when appropriate, so the conversation never stalls waiting for a full background workflow.

Why both matter: live customer conversations cannot depend on completing an unrestricted internet search every time a question arises. ANDIP LIVE combines precomputed intelligence with targeted real-time verification.
04 — Architecture Preview

Separation between voice communication and supporting intelligence execution

Two connected lanes allow the voice experience to continue while supporting work progresses under a deadline.

Dual-lane architecture: conversation lane and intelligence lane The conversation lane runs from the customer question to the primary agent, then a partial update, then the response. The intelligence lane runs from the Live Decision Broker through parallel tasks to the evidence and policy layer, and feeds back into the conversation lane as a partial update. CONVERSATION LANE CUSTOMER QUESTION Unexpected request PRIMARY AGENT Clarify and acknowledge PARTIAL UPDATE First useful evidence RESPONSE Explain or act INTELLIGENCE LANE LIVE DECISION BROKER Set deadline and task plan PARALLEL TASKS APIs, data, specialist agents EVIDENCE + POLICY Verify, rank, authorize
05 — Industry Direction

One intelligence layer. Multiple industries.

The initial product direction focuses on customer-facing conversational systems where timely external information can materially improve service quality.

Proposed use cases. Industry-specific integrations, data authorization, and validation remain required before any commercial deployment.

06 — Development Path

A measurable path to community alpha and launch

Each gate requires reproducible evidence. Dates are planning targets, not guaranteed release commitments.

Now Architecture and Early Engineering Define request, evidence, policy, and update schemas
Build Broker and parallel execution Prototype one voice-agent request with incremental results
Q1 2027 Community Alpha Reproducible hotel-rate demonstration and Reddit outreach
Q2 2027 Target Launch Subject to technical validation and operational readiness

One voice speaking. Many specialized agents working.

Verified information arriving when needed. Business decisions remaining under appropriate control. ANDIP LIVE is inviting research collaboration, technical partnerships, and early community alpha interest.

Community Alpha

Q1 2027 — narrow, reproducible demonstration

Target Launch

Q2 2027 — subject to validation and readiness