Vikash P

Vikash Pal is an AI/ML Engineer at ScholarEase and Editor for AIML Insights, focusing on machine learning, applied AI workflows, and practical implementation.

How Agentic AI Handles Multi-Step Decision making

Agentic AI, Blog /
how Agentic AI handles multi-step decision making workflow showing goals, planning, tool use, memory, feedback loops, evaluation, observability, and human approval

How Agentic AI Handles Multi-Step Decision Making: Goals, Task Decomposition, Planning, Tool Use, Memory, Feedback Loops, Escalation, and Safe Execution Agentic AI handles multi-step decision making by turning a goal into smaller decisions, planning the next step, using tools, observing results, updating context, and deciding whether to continue, replan, escalate, or stop. Unlike a standard […]

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Harnesses in Long-Running AI Agents Explained

Agentic AI, Blog /
harnesses in long-running AI agents showing tools, memory, state checkpoints, context, observability, verification, guardrails, and human approval

The Role of Harnesses in Long-Running AI Agents: Tools, Memory, State, Context, Observability, Verification, and Safety Controls Harnesses in long-running AI agents are the execution layers around an AI model that help agents use tools, manage memory, preserve state, build context, recover from failures, verify outputs, and stay observable. A strong harness turns a capable

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Document AI Tools Compared: Best OCR and PDF AI Platforms

Multimodal AI, Blog /
Document AI tools comparison dashboard showing OCR, PDFs, invoices, forms, tables, extraction panels, validation checks, and enterprise workflow automation

Document AI Tools Compared: Best Platforms for OCR, Forms, Tables, and PDF Workflows Document AI tools help businesses extract, understand, summarize, and automate information from PDFs, invoices, receipts, forms, contracts, scans, tables, and reports. The best choice depends on whether you need cloud APIs, enterprise intelligent document processing, invoice automation, PDF AI assistance, custom extraction,

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Image Capable LLMs Compared: Best Vision Models

Multimodal AI, Blog /
Image capable LLMs comparison dashboard showing screenshots, documents, OCR, charts, visual reasoning, model scorecards, and developer API workflows

Image Capable LLMs Compared: Best Models for Images, Screenshots, Documents, and Visual Reasoning Image capable LLMs are language models that can understand images along with text prompts. The best options depend on the workflow: GPT-5.5, Gemini, and Claude are strong hosted choices, while Qwen3-VL, Llama 4, InternVL3, Pixtral, and PaliGemma 2 are important open or

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Agentic AI Design Patterns Explained: How to Build Reliable AI Agent Applications

Agentic AI, Blog /
Agentic AI design patterns dashboard showing workflows, routers, planning loops, tools, multi-agent systems, human review, observability, and safety controls

Design Patterns for Building Agentic AI Applications: Workflows, Routers, Planning Loops, Tools, Memory, Multi-Agent Systems, Human Review, and Safety Controls Design patterns for building agentic AI applications are reusable architecture choices that help developers structure agents, workflows, tools, memory, handoffs, loops, and human review. They matter because agentic AI apps are harder than simple chatbots:

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How Long-Running Agentic AI Systems Stay on Track

Agentic AI, Blog /
how long-running agentic AI systems stay on track:Long-running agentic AI workflow showing state checkpoints, memory updates, tool calls, drift warnings, monitoring, recovery, and human approval

How Long-Running Agentic AI Systems Stay on Track: State, Checkpoints, Memory, Monitoring, Recovery, Human Review, and Safe Stopping Conditions Long-running agentic AI systems stay on track by preserving state, using checkpoints, managing memory, controlling context, monitoring traces, validating tool calls, limiting loops, recovering from failures, and escalating risky decisions to humans. Without these controls, long-running

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Tool Use in Agentic AI: Functions, APIs, Actions

Agentic AI, Blog /
Tool Use in Agentic AI:Agentic AI tool use dashboard showing function calling, API connectors, databases, code tools, external actions, permissions, audit logs, and human approval

Tool Use in Agentic AI: Function Calling, APIs, External Actions, Tool Routing, Permissions, Risks, and Safe Workflow Design Tool use in agentic AI is how AI agents move from generating answers to performing useful work. Through function calling, APIs, databases, code tools, search, calendars, CRMs, and workflow systems, agents can retrieve data, update systems, trigger

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Multimodal AI Model Comparison: Best Models

Multimodal AI, Blog /
Multimodal AI model comparison dashboard showing text, image, audio, video, document analysis, model scorecards, benchmarks, and developer API workflows

Multimodal AI Model Comparison: Best Models for Text, Images, Audio, Video, and Documents A useful multimodal AI model comparison should focus on workflow fit, not only benchmark scores. GPT-5.5, Gemini, Claude, Qwen3-VL, Llama 4, InternVL3, and PaliGemma 2 serve different needs across image reasoning, document analysis, video understanding, OCR, open deployment, developer APIs, and enterprise

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Best Image Understanding Models in 2026 Compared

Multimodal AI, Blog /
1. Best image understanding models comparison dashboard showing OCR, document analysis, screenshots, charts, visual reasoning, and AI vision scorecards

Best Image Understanding Models in 2026: Top AI Vision Models Compared The best image understanding models in 2026 depend on the task. GPT-5.5, Gemini, and Claude are strong hosted options for image reasoning and documents, while Qwen3-VL, Llama 4, InternVL3, and PaliGemma 2 are important open or lightweight choices for developers building vision-language AI apps.

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Memory in Agentic AI Systems Explained

Agentic AI, Blog /
Memory in Agentic AI Systems:Agentic AI memory architecture showing short-term context, long-term memory, retrieved documents, tool results, user preferences, and governance controls

Memory in Agentic AI Systems: Short-Term Context, Long-Term Memory, State, Retrieval, Personalization, Risks, and Design Patterns Memory in agentic AI systems is the mechanism that helps AI agents keep track of task context, previous steps, tool results, user preferences, and reusable knowledge. Short-term memory supports the current session or workflow. Long-term memory persists useful information

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