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DidWork Review

DidWork provides a service for verifying the completion and accuracy of tasks performed by agents through independent evidence, enhancing autonomy and reducing manual supervision.

shipped Sep 25, 2026freemium
Monthly visits1/mo
DidWork — product screenshot

Why it matters

1Offers a freemium pricing model with a free tier.
2Includes an API for programmatic integration.
3Provides 1,500 free verifications per month.
4Features integrations with platforms such as Stripe, GitHub, and Slack.

About DidWork

Business Model
Subscription SaaS
Usage Pricing
$0.01 per verification
Free Credits
1,500 verifications/month
Platforms
Web, API
Target Audience
Businesses using automated agents for various tasks.

Pricing Plans

Free
$0 / monthly
  • • 1,500 verifications/month
  • • All 38 claim types
  • • MCP server, SDKs, and API
  • • One watch, hourly
Pro
$49/month
  • • 2,500 verifications included
  • • $0.01 each afterward
  • • Unlimited watches, down to 5 minutes
  • • 1 year of evidence retention
Enterprise
Custom / Custom
  • • Committed volume and SLAs
  • • Private adapters
  • • Longer evidence retention
  • • Security review support

Cost Examples

  • • First 1,500 checks each month are free
  • • Pro plan adds $49/month for additional verifications

Specs

API Available

Yes, public API

overview

What is DidWork?

DidWork is an AI task verification tool that enables businesses to ensure the completion and accuracy of tasks performed by automated agents. It provides independent evidence to verify outcomes against expected results, thereby enhancing agent autonomy and reducing the need for manual oversight in operational workflows.

features

Key Features of DidWork

DidWork offers a suite of features designed to provide robust verification and supervision for automated agents. These capabilities ensure that tasks are executed as intended, supporting various operational requirements.

  • Independent verification of agent task completion and accuracy.
  • Automated supervision to reduce manual oversight.
  • Capability Trust mechanisms for reliable agent performance.
  • Multiple integrations with platforms like Stripe, GitHub, and Slack.
  • Flexible pricing plans, including a free tier and usage-based options.
  • API documentation available at https://didwork.sh/docs for programmatic access.

use cases

Who Should Use DidWork?

DidWork is designed for businesses and developers who deploy automated agents and require reliable verification of task execution. Its capabilities are applicable across various operational contexts where agent performance and accuracy are critical.

  • Businesses utilizing automated agents for diverse tasks, requiring verification of completion and accuracy.
  • Developers needing to validate API endpoint responses and ensure correct data processing.
  • Organizations implementing workflow automation, seeking to monitor and confirm agent actions in real-time.
  • Teams aiming to enhance the autonomy of their agents by providing a trusted verification layer, reducing manual checks.

how to use

How to Use DidWork

To begin using DidWork, users can sign up for an account and configure verification checks for their automated agents. The platform supports integration with existing workflows via its API and various third-party services.

  • 1Sign up for a DidWork account, starting with the free tier.
  • 2Define the tasks performed by your agents and their expected outcomes.
  • 3Configure verification checks within the DidWork platform to monitor agent performance.
  • 4Integrate DidWork with existing systems using its API or supported integrations like GitHub or Jira.
  • 5Monitor real-time verification results to ensure agents execute jobs as intended.
  • 6Adjust verification parameters and agent workflows based on performance data.

pricing

DidWork Pricing & Plans

DidWork operates on a freemium model, offering a free tier and tiered subscription plans. The pricing structure includes a base monthly fee for higher tiers and a usage-based charge for verifications beyond the free allowance.

  • Free: $0 per month, includes 1,500 verifications.
  • Pro: $49 per month, for additional verifications beyond the free tier.
  • Enterprise: Custom pricing, tailored for larger organizations with specific needs.
  • Usage Pricing: $0.01 per verification after the initial 1,500 free checks per month.

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Pros

  • +Provides independent verification of agent task completion, enhancing reliability.
  • +Reduces manual supervision through automated monitoring of agent performance.
  • +Offers a freemium model with 1,500 free verifications per month.
  • +Features an API and integrations with common development and business tools (e.g., GitHub, Slack).
  • +Supports a general framework for task verification across various agent types and workflows.

Cons

  • −Usage-based pricing of $0.01 per verification can accumulate costs for high-volume users beyond the free tier.
  • −Primarily focused on task verification, not comprehensive AI model testing or prompt engineering during development.
  • −Requires integration and configuration to align with specific agent workflows and expected outcomes.
  • −The 'Enterprise' pricing tier requires custom negotiation, lacking transparent public pricing.

Similar Tools

DidWork vs Competitors

DidWork distinguishes itself in the AI tool landscape by focusing specifically on the operational verification of agent task completion through independent evidence. While other tools address aspects of AI model testing and evaluation, DidWork provides a service for continuous, post-deployment validation.

1

Focuses on testing and evaluating prompts and LLM outputs with various assertions and metrics, allowing for comparison across different models and prompts.

Promptfoo is primarily a developer tool for testing and iterating on LLM agent outputs during development. DidWork appears to be more geared towards continuous, operational verification of deployed agents, providing a service for ongoing task validation.

2

Specifically designed for evaluating Retrieval Augmented Generation (RAG) systems, measuring aspects like faithfulness, answer relevance, and context recall.

RAGAS is highly specialized for a particular type of AI agent (RAG-based), offering deep, domain-specific metrics. DidWork provides a more general framework for verifying tasks across potentially different types of agents and workflows.

3

An open-source platform for testing AI models, including LLMs, focusing on robustness, fairness, and performance, with a library for programmatic evaluation.

Giskard offers a broader AI model testing suite, including LLM evaluation capabilities that can be adapted for agent verification. DidWork is more narrowly focused on verifying task completion and accuracy through independent evidence for agents in an operational context, rather than comprehensive model testing.

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