EverOS vs. past.dev Comparison Chart

Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.

LM-Kit.NET is a complete local AI runtime for .NET that lets engineering teams ship AI-powered features without cloud dependencies, per-token costs, or data leaving the network. Most .NET AI integrations stop at inference. LM-Kit.NET covers the full range of capabilities production applications actually need: agentic workflows with tool calling, planning, and memory; document intelligence with OCR and structured extraction; retrieval-augmented generation with built-in vector storage; multilingual speech-to-text; vision and multimodal understanding; text analysis with classification, NER, PII extraction, and sentiment; and text generation with translation, summarization, and constrained output. Ships in one NuGet package, runs in-process with no sidecar services, and works across all major hardware acceleration backends. Drop-in replacement for Semantic Kernel through its Microsoft.Extensions.AI compatibility layer.

NeuBird is the governed center of agentic operations: one secure, audited connection to your telemetry and your LLMs, with a memory of every investigation, so your engineers, your leaders, and your own agents all start from what the company already knows.

Air gives your team's work a memory. Every asset, version, and approval is tracked in one place, and that context powers everything that happens next: finding what's approved in seconds, adapting it for any channel, and scaling it everywhere without breaking brand. Air connects the creative team that makes the work to the marketing team that multiplies it, with a shared system of record keeping everyone aligned.

Dragonfly is a drop-in Redis replacement that cuts costs and boosts performance. Designed to fully utilize the power of modern cloud hardware and deliver on the data demands of modern applications, Dragonfly frees developers from the limits of traditional in-memory data stores. The power of modern cloud hardware can never be realized with legacy software. Dragonfly is optimized for modern cloud computing, delivering 25x more throughput and 12x lower snapshotting latency when compared to legacy in-memory data stores like Redis, making it easy to deliver the real-time experience your customers expect. Scaling Redis workloads is expensive due to their inefficient, single-threaded model. Dragonfly is far more compute and memory efficient, resulting in up to 80% lower infrastructure costs. Dragonfly scales vertically first, only requiring clustering at an extremely high scale. This results in a far simpler operational model and a more reliable system.

Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines. Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications. Integrate Compute with other Google Cloud services such as AI/ML and data analytics. Make reservations to help ensure your applications have the capacity they need as they scale. Save money just for running Compute with sustained-use discounts, and achieve greater savings when you use committed-use discounts.

SearchUnify is an enterprise Agentic AI platform that unifies enterprise knowledge and powers autonomous AI agents across the customer support lifecycle. Built on SearchUnifyFRAG™ (Federated Retrieval Augmented Generation) and Agentic RAG, it delivers contextually accurate, real-time responses across self-service, agent-assisted, and automated support workflows. Its product suite includes Cognitive Search, SearchUnifyGPT™, SUVA (Virtual Assistant), Knowbler, and Agent Helper. The Agentic AI Suite deploys eight specialized AI Agents handling case resolution, case classification, escalation management, knowledge management, case quality auditing, and L2 technical workflow automation. SearchUnify supports BYOLLM, enabling LLM flexibility without vendor lock-in, and uses Model Context Protocol (MCP) for secure enterprise integrations. A built-in governance layer provides role-based access control, PII masking, and compliance with ISO 27001, HIPAA, and SOC 2.

RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments. RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree.

SBS Asset Finance is a cloud-native, modular platform built for banks, captives, and specialist lenders managing asset-based finance. It supports the full financing lifecycle, from digital onboarding and credit decisioning to loan servicing, portfolio management, risk control, and digital audit. SBS Asset Finance can be deployed end-to-end or module by module, making it easy to modernize legacy systems without a full replacement. The platform automates core processes, improves data visibility in real time, and integrates seamlessly with existing ecosystems through open APIs. Designed for scale and operational control, SBS Asset Finance helps lenders reduce processing costs, manage risk consistently across portfolios, and adapt quickly to new asset classes, markets, and regulatory requirements. Delivered as a SaaS solution with an evergreen upgrade model, it ensures predictable costs, minimal maintenance, and long-term scalability.

Dartican’s CompAccelerator is a robust compensation planning solution designed to provide the agility needed to address the challenges of today’s dynamic business environment. CompAccelerator guides managers in allocating salary, bonus, and long-term incentives, thus advancing transparency, expanding visibility and improving accuracy all while reducing the time and cost to setup and administer your planning cycle. This feature-rich and highly scalable software’s intuitive administration delivers sophisticated capabilities that are simply and quickly deployed for unmatched business agility. CompAccelerator is backed by readily available support staff with strong corporate compensation experience at your disposal.