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Agently vs Due Diligence Agents

Agently and Due Diligence Agents are both ai agent apps tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Agently

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.

Due Diligence Agents

Due Diligence Agents

The tool runs parallel analysis across Legal, Finance, Commercial, Technology, Cybersecurity, HR, Tax, Regulatory, and ESG workstreams — domains that siloed consultants hand off sequentially, bleeding weeks in the process. Each agent cross-references findings against the others, so a revenue concentration risk in the commercial workstream gets flagged against the indemnification language in legal without a human manually connecting the dots. Outputs land in Excel and Word with citations intact, ready for an IC memo. The knowledge compounds across deal runs, so repeat buyers in the same sector start with context the first team had to build from scratch. The ceiling appears when your data room contains formats the parser does not handle cleanly — and at that point, teams are pre-processing documents manually before the agents ever see them.

AttributeAgentlyDue Diligence Agents
PricingPaidFree
Price$69/mo
Free trialNoNo
Open sourceNoYes
Has APINoNo
Self-hosted optionNoYes
PlatformsWebPython (Linux, macOS, Windows via Docker or local install)
Pros
  • Two-way OAuth integrations across 100+ tools with live sync, so agents act on current data rather than stale snapshots that make automated decisions unreliable.
  • Outputs land as real files — docs, sheets, decks, gated pages, CSV exports — which means the agent's work is immediately usable rather than requiring a human to translate a chat response into an action.
  • Jarvis orchestrates multiple specialized agents in parallel, so a single trigger (a failed Stripe charge, a renewal risk flag) can simultaneously update HubSpot, send a Gmail sequence, and post to Slack without manual handoffs.
  • Live activity board shows every task in triggered, running, and shipped states, so you have an audit trail of what ran and when — without that, debugging an automated sequence that misfired requires guesswork.
  • Predefined agent roles (Revenue, Support, Growth, Ops, Briefer, Researcher) cover the recurring work that consumes the most meeting time at early-stage teams, so setup targets high-frequency pain rather than requiring teams to design workflows from scratch.
  • 13 agents analyze nine domains in parallel rather than sequentially, which means a workstream that would take a consultant team weeks to hand off completes in a fraction of the calendar time.
  • Every finding is traced to an exact page and quote in the source document, so IC memos and advisor reports arrive with citations pre-built rather than requiring a second pass to source claims.
  • Cross-domain synthesis flags when a finding in one workstream changes the risk weight of a finding in another — catching the legal exposure a pure financial review would miss.
  • Knowledge compounds across deal runs, so teams analyzing targets in a recurring sector carry prior context forward instead of rebuilding domain understanding from zero each time.
  • Self-hostable under Apache-2.0, which means data room documents stay inside the team's own infrastructure rather than transiting a third-party SaaS layer — a requirement many corporate legal and compliance functions enforce.
Cons
  • The agent roles are predefined and the vendor describes no mechanism for custom agent logic — teams whose workflows involve branching based on domain-specific rules (e.g., different recovery sequences per customer segment) hit this ceiling immediately and have no documented workaround short of manual intervention.
  • No self-hosted option exists, and there is no free tier — teams in regulated industries or with data residency requirements cannot evaluate or deploy this tool, and will move to a competitor that supports on-premises deployment.
  • The orchestration model is opaque: the vendor shows a live activity board but does not describe how to inspect or override a Jarvis decision mid-run, which means when an agent takes the wrong action on a live customer record, the recovery path is unclear and potentially damaging.
  • Non-standard document formats — scanned PDFs without clean OCR, nested Excel models, heavily formatted legal exhibits — require manual pre-processing before the agents can operate on them; on data rooms where half the documents need cleaning, the time compression the tool promises shrinks significantly.
  • The tool has no API surface, so teams that want to trigger analysis from an existing deal management system or integrate outputs into a live workflow dashboard cannot do so without forking the codebase and building the integration themselves.
  • The external LLM dependency means cost and latency are governed by whichever provider the team configures — a large data room routed through a rate-limited API will queue, and teams running multiple deals in parallel against the same LLM endpoint will feel that ceiling; at that point, teams with the infrastructure budget move to a dedicated model deployment rather than a shared API.
Bottom line

Agently is paid while Due Diligence Agents is free; Due Diligence Agents is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Agently and Due Diligence Agents?

Agently is Paid, while Due Diligence Agents is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Agently better than Due Diligence Agents?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

Agently vs Due Diligence Agents: which should I pick?

Pick Agently if its pricing model, openness, or platform fit matches your constraints; pick Due Diligence Agents otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.