Assembled is the only unified platform for staffing and managing your human and AI support team.
AI for world-class support operations
Assembled is the only platform that unifies AI agents and intelligent workforce management to power fast and flexible support operations. Built for scale, we help teams automate over 50% of customer interactions, forecast with 90%+ accuracy, and optimize staffing across in-house and BPO teams. Orchestrate every chat, email, or call, balancing workloads between human and AI agents in real time — without sacrificing quality or control. Trusted by Stripe, Canva, and Robinhood, Assembled transforms support from a cost center into a strategic advantage. Our Workforce and Vendor Management tools connect forecasting, scheduling, and performance for smarter staffing decisions. AI Agents automate conversations across channels with your workflows and brand voice. AI Copilot empowers agents with real-time guidance, suggested replies, and one-click actions for faster, higher-quality resolutions.
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CompanyCam is a photo-based solution created for contractors, by contractors.
Take photos, track progress, and collaborate on tasks with job site management tools and AI shortcuts for every phase of any project.
Take unlimited photos—which are location and time-stamped, sent to the cloud, and stored securely. Every photo is organized by project and instantly available to your team, allowing you to see what’s going on anytime, anywhere. Annotate photos with drawings, arrows, comments, tags, and voice notes, and create project timelines, photo galleries, reports, and transformation photos through the app. Sharing photos with customers and insurance adjusters has never been easier, and keeping your entire process organized has never been simpler.
Mimosa is a modeling and simulation platform, covering the process from building conceptual models to running the simulations. The specification uses ontologies and an extensible set of formalisms for the dynamics. The simulation kernel is based on DEVS.
PetriNetExec a library for embedding Petri Nets into Java applications
Briefly said, PetriNetExec is an open-source Java library which allows you to embed Petri Nets into your Java application.
Using PetriNetExec you can define places and transitions, connect them using arcs and inhibitors, define the initial marking and then fire events and see how tokens flow into the network.
* PetriNetExec does not provide a GUI for editing the network nor will it provide in the near future. That is not really a feature :-) but to those of you able to cope with this...
PerMoTo is a Performance Modelling Tool suite for decision support in the capacity and performance management of distributed transaction processing systems based on Queueing Theory and Discrete Event Simulation.
Pylon is an All-in-one B2B Support Platform for modern B2B businesses.
Pylon is a modern support system that integrates with all B2B channels like Slack and Team.
We bring together everything a post-sales teams team needs including a ticketing system, B2B omnichannel integrations (Slack Connect, Microsoft Teams), modern chat widget, knowledge base, AI support bot, account management, customer marketing, and more.
Metaquokka is a highly configurable xml editor, currently available as Gridsphere portlet. Besides the default format, there is suppoert for ESysXML, a simulation description scheme for a geodynamics framework. Supports Generic Mapping Tools rudimentary.
The Network Security Response Framework (NSRF) allows for testing different computer security response engines and methodologies. It supports simulated and real: Intrusion Detection Systems (sensors), Attacks, and Responses.
MEM Net - Mote EMulator Network.
This project will focus on:
1) MEM - Wireless Sensor Node (mote) emulator
2) MEM Net - network of emulated motes
So far, the only released package is visual-sim-slides.
More comming next !
It's a Cat and Dog game,we develop the Inner AI strategy for the Dog and we also code the strategy of the cat in order to simulate the user. Furthermore we use Artificial Neural Network to build the experiment