LOGISTICS AI SOLUTIONS

TRANSFORMATIVE AI SOLUTIONS

Speed-up RFQs, enhance fleet management and optimise risks.

Start with our Logistic AI Agents today.

STATUS QUO

84% of logistics experts said AI will transform their organisation

The adoption rate of generative AI has doubled in traditional businesses

Plan to invest in AI-driven logistics solutions within the next 2 years

Of business leaders reported positive ROI from AI investments

use cases

AI Tools for Logistics

Automated RFQ

Fetches real-time data and answers with human-like quotes right away.

Live Data Integration

Streamlines information for fleet and cargo availability for better tracking.

24/7 Sales & Support

Streamline support and boost sales with AI-driven virtual assistants.

INSTANT PRICE QUOTES

Automated RFQ

Fetches real-time data and answers with human-like quotes right away.

Live Data Integration

Streamlines information for fleet and cargo availability for better tracking.

24/7 Sales & Support

Streamline support and boost sales with AI-driven virtual assistants.

FLEET OPTIMIZATION

Smart Demand Management

Optimising and matching available capacity with fluctuating demand from clients.

Optimising Costs

Giving you real-time notifications and suggestions on expense management.

Integrated with Your Management Platform

Seamlessly connect your existing Fleet management software to our AI Agents via API.

OPERATIONAL EFFICIENCIES

Cost & Market Volatility

Better predict fuel prices, maintenance and other expenses for optimal budgeting and cost control.

Risk Management

Optimise insurance liabilities, theft and unexpected disruptions with AI-powered risk management.

Workforce Management

Make smarter, data-driven decisions powered by AI logic embedded in your operations.

Infer

Shaping the Future of Work

A new are or AI employees will emerge handling all mundane tasks to more complex strategical goals.

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 async def talk_to_llm(self, stream: rtc.AudioStream):
  async for event in stream:
    alt = event.alternatives[0]
    msg = LLMMessage(role=LLMMessageRole.User, content=alt.text)
    llm_stream = self.llm.send_message(msg)

***stream tokens to client
  async def process_llm_tokens(self, stream: LLMStream):