Introducing JigsawStack Deep Research
What is Deep Research?
JigsawStack’s Deep Research is an open source framework performing for multi-hop, AI-assisted research. The framework orchestrates large language models (LLMs), recursive web searches, and structured reasoning to generate comprehensive, evidence-backed reports via our deep-research SDK. Designed for developers, researchers, and AI agents. We aim to automate the kind of deep inquiry that typically takes hours or even days.
Get a quick start by trying out our SDK here: https://github.com/JigsawStack/deep-research
Core Concepts
| Concept | Description |
|---|---|
| Deep Thinking | The system breaks down a question into logical parts, reasons through them independently, and synthesizes an answer. |
| Deep Research | The system performs multi-hop, focused web searches, compares the findings, and composes an evidence-backed answer |
How JigsawStack Implements Deep Research
Deep Research performs the following:
- Research Plan, decomposing complex query into logical subtopics and objectives.
- AI Web Searches via JigsawStack API, generating context and extracting key points from the web
- Multi-Model Reasoning and Decision Making, the framework adapts its strategy based on findings, filling knowledge gaps as needed
- Report Generation, including structured content and source attribution for traceability
Fully Customizable
One of the core strengths of JigsawStack’s Deep Research is how deeply customizable it is.
- Precise Control Over Depth & Breadth
- Report Length Targeting - Configure your desired report length with soft and hard output limits
- Developer-Friendly Debugging - Enable detailed logging for developers
- Model Modularity - Mix and match AI Providers based on their strengths
Current Market and the Challenges of Deep Research
While many are pushing boundaries, current implementations face a few common challenges:
- Citation Accuracy & Transparency
- Limited Customization & Developer Control
- Closed-Source & Opaque Systems
- Limited Integration Options
We aim to address these pain points, making it a research platform you can build on.
Comparisons
| JigsawStack | OpenAI | Perplexity | |
|---|---|---|---|
| Citation Transparency | ✅ Strong. Ensures source traceability with comprehensive bibliographies. | ⚠️ Partial. While citations are provided, some users report occasional inaccuracies or reliance on less authoritative sources. | ✅ Strong. Curates a list of relevant URLs with titles and descriptions for each research task. |
| Customization & Control | ✅ Full. Allows developers to configure every stage, including depth, models, and formatting. | ❌ Limited. Users have minimal control over the research process and output formatting. | ⚠️ Limited. Offers some customization, such as model selection, but lacks deep configurability. |
| Open Source | ✅ Yes. Fully open-source. | ❌ No. | ❌ No. |
| API / SDK Access | ✅ Yes. accessible SDK for developers to plug and play into their workflow. | ⚠️ Internal use only | ⚠️ Limited / closed |
| Limitations | Slower runtime by design; limited to public content only. | May produce inconsistent information and occasionally cite less authoritative sources. | Lacks creative flexibility and may provide less engaging conversational responses. |
Real World Examples
Write a research paper talking about diffusion for LLMs and how it might affect the future in technology?
What is the largest order of a non-cyclic torsion subgroup of an elliptic curve over \mathbb{Q}(\sqrt{-3})\)
Improvements to JigsawStack’s Deep Research
While Deep Research provides powerful automation for complex inquiry, it’s not without its trade-offs and design challenges:
- Runtime Trade-offs - deep research deliberately shifts away from the fast-but-shallow answers towards deep and completed ones.
- Exclusive to Public Information - we are unable to access paywalled research papers, private documents, or internal knowledge bases
- Sources Discrepancy - Some sources provided are not quoted on the report. Even if a URL isn’t directly cited in the final report, it may still play a critical role in shaping the system’s reasoning.
- Evolving output format - The first stage of Deep Research prioritizes correctness, structure, and citations. But the ideal report format — tone, length, granularity — will vary by user and use case. We’re actively evolving the output schema based on real-world feedback to support!
Next Steps
As we continue to evolve Deep Research, the next major milestone is full integration into JigsawStack’s web search API.
Currently, Deep Research uses JigsawStack’s search API for retrieving public content. Going forward, we’re expanding this connection to make the research experience even more seamless and intelligent.
👥 Join the JigsawStack Community
Have questions or want to show off what you’ve built? Join the JigsawStack developer community on Discord and X/Twitter. Let’s build something amazing together!