⚡ Scoreboard · September 6, 2026
AI Agents Scoreboard
Agent frameworks and end-user AI agent apps ranked by verified-data score. Built for builders who need a current shortlist, not a directory dump.
Ranked by AIDiveForge's verified-data score: data completeness, verification recency, community rating, and real visitor engagement. How we rank · No tool can pay for placement.
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1
NoInfra
The vendor delivers pre-configured, hosted agents across a set of templated use cases: study summarization, job application tracking, spreadsheet cleanup, meeting prep, and sandbox code execution. You open a workspace and the agent is already running — no keys, no servers, no config files. The managed runtime abstracts token provisioning server-side, so users see a balance and status indicator rather than provider credentials. Where this model breaks: the compute ceiling is fixed per tier, and teams whose workloads outgrow the allocated vCPU and RAM have no self-hosted escape hatch — they either upgrade or leave.
Paid $19.99/mo and upVerified Jul 9, 202610.4 score -
2
EverMemOS
EverMemOS, built by EverMind, is a memory infrastructure layer that gives AI agents persistent, inspectable, and portable memory across sessions, platforms, and model providers. The vendor describes multimodal ingestion, so agents can encode not just text exchanges but structured context from multiple input types. Self-hosted deployments run under an Apache 2.0 license, which means teams with data-residency requirements can own the stack entirely. The ceiling appears when memory graphs grow dense — community reports suggest retrieval latency climbs before tuning is required, and teams building high-throughput customer support pipelines report needing to manage memory pruning manually. Teams that need memory to double as a full observability or analytics layer find they are adding a second tool alongside it.
Paid APISelf-hostedVerified Aug 16, 202610.2 score -
3
Vora IQ - StartupOS for Founders
The core workflow starts with your idea or existing business: Vora IQ runs a viability analysis — market demand, competitor landscape, real signal — then generates a living roadmap that reprioritizes as your business moves. Agents covering strategy, finance, marketing, legal risk, and social content operate in the context of your specific business, so advice is not generic. The daily task queue is the most practical output: you open the tool and it tells you exactly what to do next. Where it shows strain is depth — a solo founder validating a SaaS idea gets real value, but a team that needs complex financial modeling with custom assumptions or nuanced legal review will find the agents hit their ceiling before a specialist would.
Paid $29.99/mo or $180/yrVerified Aug 16, 202610.0 score -
4
Xalgorix
The core loop is detect, chain, verify: the agent runs reconnaissance through injection through authentication testing, then executes a dedicated validation phase before anything reaches your report. On a public deliberately-vulnerable target, the vendor documents 9 verified findings including a CVSS 9.8 RCE in 17 minutes. The REST API and cron-style scheduling let security teams wire scans directly into CI/CD gates, so releases block on verified findings rather than scanner noise. Where the architecture shows its limits: scan depth and concurrency are credit-gated, and teams running continuous coverage across a wide attack surface will need to budget credits carefully. Self-hosted deployment is listed as an option for teams with data-residency requirements.
Paid Open source from $1 per scanAPISelf-hostedVerified Jul 8, 20269.7 score -
5
Open-Kritt
The tool runs parallel AI agents across a codebase, so vulnerability discovery that would serialize into hours on a single-context scan distributes across concurrent analysis threads. It targets security researchers and bug bounty teams who need to sweep repositories at scale, not review a function at a time. Self-hosting is supported under AGPL-3.0, which means your code and findings never leave your infrastructure — a requirement for any org with compliance constraints. The open-source core is inspectable and forkable, but managed scans are a paid-only feature, so teams that want the hosted workflow face a significant spend threshold. The page describes GitHub integration as a first-class path, making it a practical fit for teams already running security workflows inside existing CI infrastructure.
Paid Open source Self-hostedVerified Jul 21, 20269.6 score -
6
Brain Memory
Brain Memory stores agent decisions as Markdown files with YAML frontmatter, organized in a directory tree you can browse in any file explorer — no opaque vector database, no embeddings you cannot audit. Strength decays on an Ebbinghaus exponential curve and rebuilds each time a memory is recalled, so the architecture you revisited three times stays sharp while the one-off experiment fades. The benchmark vendor cites shows 100% recall on a 1,000-distractor haystack where BM25 and vector retrievers both score zero — a meaningful gap for long-running coding projects. The tool is at v0.1.0, MIT-licensed, and ships as an npm global install. That version number is not a warning to ignore: the sleep consolidation pipeline and the cross-agent sync model are genuinely novel, which means the surface area for early-stage bugs is wider than a mature retrieval library.
Free Open source Self-hostedVerified Aug 14, 20269.4 score -
7
Emem
emem stores facts as short, signed tokens — each one a content-addressed handle that any agent can carry through a summarization pass, hand to another agent on a different model or vendor, and resolve back to the exact signed bytes without trusting whoever sent them. The verify step is offline: recompute the hash and ed25519 signature yourself, no server call required. Cold resolution runs around 180 ms; warm cache hits around 10 ms, with every receipt reporting its own latency stats. The honest caveat from the vendor's own benchmarks: against a bare inline number, a single emem token costs 5.8x more context — the savings only appear when you bundle multiple facts into one round trip.
Paid Open source APIVerified Jul 23, 20269.4 score -
8
Nelieo NSP
NSP attaches to running JVM, V8, and CLR processes on Windows and exposes their internal object graphs at reported p50 latencies around 11ms — no rendering pipeline, no DOM traversal. The vendor's benchmark compares token consumption per task at roughly 580 tokens via NSP against ~14,850 tokens for a vision-model loop, which, if it holds at your workload, translates to a dramatic drop in per-workflow cost. The architecture is deterministic: agents invoke functions by memory address rather than locating UI elements, so a CSS drift or layout change does not break the execution path. The ceiling appears at runtime scope — NSP is Windows-only, covers V8, JVM, and CLR, and native-compiled binaries or runtimes outside that list get no structured access. Teams automating cross-platform or browser-agnostic workflows will hit that boundary quickly.
Paid APISelf-hostedVerified Aug 17, 20269.4 score -
9
Not Another AI Platform
HelloAI is a freemium, cloud-only AI assistant from Pixelverse that routes tasks across writing, image generation, web research with cited sources, code execution, and document analysis without requiring the user to change tools. The multi-model access means you can draft marketing copy, generate a matching visual, and verify a statistic with a sourced web search inside a single session. The free tier provides a functional entry point, but higher-volume usage and access to advanced models are paid-only features. No API is available, so any team that needs to embed HelloAI's capabilities into their own product or automate workflows programmatically hits a hard wall immediately. Self-hosting is not an option, which means your data stays on Pixelverse infrastructure with no alternative.
Paid $9/monthVerified Jun 30, 20269.4 score -
10
exployt.ai
exployt is a multi-AI orchestration platform built specifically for software developers who need to run coding agents from Anthropic, OpenAI, Google, and local models in parallel rather than in sequence. The core workflow lets a single developer assign tasks to multiple agents simultaneously, monitor their progress, and ship output without context-switching between provider dashboards. The product is in Early Access, which means the feature surface is still forming — vendor documentation confirms this explicitly. Teams that need stable, battle-tested orchestration for production systems will feel that immaturity. At this stage, exployt fits exploratory workflows better than it fits pipelines where a Monday morning spike cannot break anything.
Paid €50/mo or €100/moVerified Jun 30, 20269.3 score -
11
Agent-Talk
The protocol is deliberately minimal: one markdown file on disk, four rules, no server. Two agents take alternating turns editing a single document — not appending to a chat log, but converging toward one answer — until one proposes consensus and the other confirms it. A configurable timeout ends sessions that stall. It installs via a single npx command and works with any agent that can read and write files: Claude Code, Codex, Grok, or any model your stack already uses. The constraint is also the ceiling — this is a file-format protocol, not an orchestration platform, so anything requiring dynamic branching, parallel task distribution, or state beyond one document is out of scope.
Free Open source Self-hostedVerified Aug 14, 20269.2 score -
12
Agently
Agently connects to 100+ tools via OAuth and builds a live graph of your company's activity, then runs a set of specialized agents — Researcher, Revenue, Growth, Support, Ops, Briefer — coordinated by an orchestrator called Jarvis. Agents post Slack threads, recover failed Stripe charges, flag renewal risks, and ship formatted documents without waiting for a prompt. The output is artifacts — sheets, docs, decks, gated pages — not chat transcripts. The ceiling appears when you need conditional branching that goes beyond the predefined agent roles; the vendor describes no mechanism for custom agent logic or self-hosted deployment. Teams with non-standard workflows will feel the constraint.
Paid $69/moVerified Jul 15, 20269.2 score -
13
Nimbus
Nimbus runs a ReAct planning loop that maps a natural-language request to actual cloud actions: querying live AWS or GCP telemetry, generating infrastructure changes, opening PRs on connected repositories, and updating shared architecture diagrams. Approval gates sit between the agent's plan and execution, so nothing ships without a human sign-off. That model works well for incident diagnosis and routine cost optimizations. Where it strains is on cross-account, deeply custom IAM environments — the agent's tool set reflects the scaffolding its maintainers have wired up, and anything outside that surface area requires you to extend it yourself. Self-hosting via Docker or source install keeps sensitive cloud credentials off third-party infrastructure, which is the primary reason platform teams choose it over a SaaS alternative.
Paid Open source APISelf-hostedVerified Jul 8, 20269.2 score -
14
Willder
The platform runs agents on three shared layers: a persistent memory graph, OS-grade access control, and a coordination layer that lets agents hand off work without rebuilding state. A research agent writes findings into shared memory; a drafting agent picks them up without being re-briefed. Every action lands in an approval inbox before it moves — you sign off, nothing ships without you. The vendor states retrieval from the graph-based memory is up to 35% more precise than vector-only search, citing a Lettria cross-sector study. The ceiling appears early: the free tier caps at one seat and one agent, and the concurrency limit is fixed at five parallel agents regardless of plan.
Paid $99/mo for Team (first 20 teams at $9/seat locked)Verified Jul 2, 20269.2 score -
15
adris.tech
adris is a desktop app for Windows and Linux that bundles eight modules — AI agents, automation, a code editor, local model hosting, a credential vault, DNS-level threat blocking, cross-machine RAM pooling, and a shared knowledge graph — under one login. The agents (called Krew) research prospects and verify contacts in a live browser, then hand results directly to automations that push to Slack, Sheets, or Notion on schedule. Everything stores locally in SQLite; credentials never leave the device. The ceiling appears when you need a public API to connect adris to an existing internal system — the vendor does not list one. Teams that need to pipe agent output into a custom backend will hit that wall fast.
Paid from ₹0Self-hostedVerified Jul 20, 20269.0 score -
16
AgentCaly
The core workflow is event-driven: you create or annotate a calendar event, and an agent runs a defined task at that time — pulling news, finding leads, checking flight fares, or drafting a blog outline — without you opening another app. The calendar-as-interface model removes the scheduling layer most automation tools require you to build separately. Where it strains is depth: agents suited to daily briefings and contact lookups hit their ceiling when tasks require conditional branching across more than a couple of steps. Teams that need complex multi-step decision logic will find themselves wanting a dedicated orchestration layer this tool does not provide.
Paid $15/month (PRO)Verified Jul 11, 20269.0 score -
17
Argonix
Argonix surfaces its agent, Argos, as the connective tissue between monitoring, security scanning, and cloud cost management — domains that traditionally require separate tools, separate on-call rotations, and separate budget conversations. Argos runs autonomous incident investigations, pulls root cause analysis, and can ship a pull request or trigger a scaling action without waiting for a human to translate the alert into a ticket. SRE Patrols let you schedule recurring health checks across connected systems, so gaps surface before pages do. The as-code layer means monitors and workflows live in your repo alongside your Terraform and Kubernetes configs. The ceiling appears when you need fine-grained audit trails for every autonomous action — teams with strict change-control requirements report adding approval gates that slow the autonomous loop down to something closer to assisted automation.
Paid Self-hostedVerified Aug 17, 20269.0 score -
18
Genesys
Genesys stores what you share in a causal graph you own, then surfaces that context to any app that speaks MCP — so Claude already knows what you told ChatGPT, without you repeating yourself. The graph explains its own reasoning: ask why it remembers something and you get the actual chain of connections, not a confidence score with nothing behind it. Memories fade by a scoring formula tied to relevance and reactivation, so stale data drops out without silently deleting things that still matter. The free tier caps writes at 300 stores per month — heavy users or teams running MCP agents hit that ceiling, then face a choice.
Paid Open source $0-$8/moAPISelf-hostedVerified Jul 22, 20269.0 score -
19
Jaybase
Jaybase stores every agent-generated fact as an immutable, time-stamped record, which means the full sequence of what an agent wrote, when, and why is always recoverable. The vendor describes it as designed for accounting, compliance, and approval workflows where you cannot afford to lose the paper trail. Because it is append-only, there is no overwrite risk — replaying a sequence from any point is a native operation. The library is self-hostable and open-source under AGPL, so it runs inside your own infrastructure without a call home. The project has a small contributor footprint, which means production teams should expect to own gaps in documentation rather than wait for the maintainer to fill them.
Free Open source APISelf-hostedVerified Jul 23, 20269.0 score -
20
Loop me in
The workflow is mechanical by design: an expert publishes a named loop with a fixed rate, the required context, and the specific judgment they return. When an agent hits that loop, it assembles context automatically and holds until the expert answers — from wherever they are. The model works cleanly for agents with clear pause points: brand reviews mid-code-generation, onboarding drop-off calls during product iteration, incident root-cause reads from logs. Where it strains is any run that needs real-time back-and-forth rather than a single bounded exchange, or any team whose agent framework does not support MCP hosts. The expert-as-contractor model is early — the vendor states V1.0.0, so directory depth and answer latency are open questions.
Paid Verified Jul 24, 20269.0 score -
21
Lunen.ai
A subject-matter expert describes what they want in plain language; Lunen drafts a structured execution plan with named tools, scoped data, and a schedule — no canvas, no YAML. Every MCP tool connection becomes a per-tool policy decision: allow it to run unattended, or pause for a human sign-off before each call. User actions and agent actions land in the same audit log, which means security reviews have a single trail to pull. The ceiling appears when teams need conditional branching between agent steps — the plain-language plan model does not surface that logic visibly, so complex multi-step dependencies require workarounds the interface does not directly support.
Paid Self-hostedVerified Jul 20, 20269.0 score -
22
ClawHire.ai
ClawHire provisions discrete AI workers — each with its own memory, document context, and connection to your existing email, CRM, and calendar stack — so the sales outreach agent that qualified a lead on Monday is the same one following up on Thursday. The vendor describes a self-checking step where each AI worker reviews its own output before acting, which matters more for document-heavy admin workflows than for simple chat. The central dashboard gives you visibility into every worker's task queue and output, with human-approval controls before anything ships. The ceiling shows up when your workflows need logic the worker can't express without developer configuration — the platform's no-code framing sets an expectation the edge cases don't always meet. No API access is available, so anything requiring custom integration past the listed connectors stays out of reach.
Paid Verified Aug 16, 20268.6 score -
23
GNT
GNT sits at the action boundary between your agent runtime and the outside world. Before a tool call executes, check_action evaluates it against your org's approved rules and returns one of three verdicts: allowed, blocked, or needs_human — along with the exact rule that decided it. Rules originate as auto-drafted PRs from a repo scan, get merged by a human on GitHub, and are re-examined nightly for staleness or contradiction. The audit trail is the point: every decision maps to an approved rule and a timestamp. The ceiling appears in regulated environments, where SOC 2 attestation is not yet issued — teams with hard compliance deadlines on that specific requirement will need to track that gap.
Paid Open source APISelf-hostedVerified Aug 14, 20268.6 score -
24
GSV
GSV deploys your AI into your own Cloudflare account — not onto a box you manage, but across an edge layer that connects every device you own into one shared context. Your laptop, home server, and phone act as a single computer, and the brain keeps running when none of them are on. Reach it through Telegram, Discord, or a terminal — wherever you already work. The tradeoff is real: GSV requires a Cloudflare Workers Paid account, which means your infrastructure is permanently coupled to Cloudflare until off-platform self-hosting ships. That roadmap item is public, but it is not yet available.
Paid Open source ~$5/mo Cloudflare + model costsVerified Jul 2, 20268.6 score -
25
Lucidos
Lucidos is a self-hosted, MIT-licensed AI OS that builds apps, dashboards, and automations from plain-language descriptions and runs them persistently on your own machine. You describe what you want — a half-marathon tracker, a language coach, a weekly digest from three APIs — and Lucidos writes it, wires it to your data, and keeps it alive without a separate deploy step. Shared long-term memory means every app and automation you add already knows your context, so complexity compounds instead of restarting at zero. The stack is Rust engine, TypeScript frontend, and a Postgres event store, so self-hosting is real infrastructure, not a checkbox. Where it breaks: the tool is early-stage and community-built, so production reliability for event-driven automations calling external APIs depends heavily on your own debugging tolerance.
Free Open source APISelf-hostedVerified Aug 14, 20268.6 score
Scores recompute as listings are verified. Sponsored placements (if any) never affect rank. Methodology · Weekly radar