FrameForge: comic-video production agent workspace
FrameForge rebuilds script2video-ai from a feature SaaS into Reallier-owned private comic-video production: new UI, demo flow, operation console, provider runtime, and automated acceptance.
This is not a fixed package menu. Everything here is a case: scenario cases explain selection by problem type, scale, complexity, and availability needs; project cases show concrete architecture, problems solved, and outcomes.
FrameForge rebuilds script2video-ai from a feature SaaS into Reallier-owned private comic-video production: new UI, demo flow, operation console, provider runtime, and automated acceptance.
A noisy, multi-tool, long-running market research workflow explains why advanced Agent systems need a Harness to control model calls, state, tools, evaluation, and replay.
Demo, engineering estimates, benchmark, and evaluation frame latency, throughput, cost, Recall@K, and evidence coverage for hiring intelligence.
Trend discovery, collection, parsing, retrieval, and quality monitoring turn public information streams into searchable, evaluable, reusable knowledge assets.
Each media type gets the right open-source processing path, then flows into one retrieval layer for cross-media semantic search.
Use awesome-selfhosted as the starting point, then review licenses, maintenance, deployment risk, security history, and operations boundaries.
For R&D, outbound, and AI application teams, govern high-latency links, auto-testing, protocol layers, exit-IP risk, and download traffic separately.
Unify website chat, WhatsApp, Telegram, and enterprise messaging into one support layer with knowledge-grounded replies and human handoff.
IT, HR, Finance, and Legal policies, SOPs, templates, and approvals become a permissioned assistant that moves from answers to actions.
Competitor, sentiment, policy, and industry signals are collected, summarized, archived, and delivered so teams read decisions instead of raw noise.
Traces, datasets, automated evaluation, CI gates, and dashboards make every prompt, agent, and RAG iteration evidence-based.
Model APIs, agents, and app entry points are tested for jailbreaks, injections, leakage, and tool abuse, then turned into remediation reports.
Q&A, collection, approvals, reporting, and tool usage become role-based workflows with human safety valves and operational governance.
OpenBB, Qlib, vnpy, local data providers, and report retrieval are selected and customized around research, quant, and private deployment needs.