Introduction to In‑Flow Research Agent for Immigration Law

Parley streamlines immigration law practice by automating intricate and evidence-driven processes. Its proprietary AI-powered Research Agent is a core component of this advancement, enabling attorneys and paralegals to automate the gathering and insertion of media metrics, salary benchmarks, and industry data directly into visa application drafts, such as O-1, EB-1, or H-1B petitions. This not only saves hours of research but elevates the evidentiary standard for filings, improving petition strength and efficiency.

What is Parley’s Research Agent?

Parley’s Research Agent is an AI-driven tool embedded within the broader Parley platform (parley.so). It automates:

• External evidence collection (e.g., news mentions, awards, salary data, industry benchmarks).

• Sourcing and summarization of third-party documentation required by USCIS for major visa categories.

• Direct referencing and citation insertion within documents drafted in Microsoft Word via Parley’s add-in.

This functionality is critical for satisfying the evidentiary requirements of petitions that hinge on demonstrating national/international recognition, extraordinary ability, or market value.

Source: LinkedIn: Introducing Parley’s Research Agent

Step-by-Step: From Query to Inserted Evidence

1. Initiate Case Drafting: Attorney selects visa type (e.g., O-1A) in Parley (Microsoft Word add-in or web portal), uploads available client documentation.

2. Evidence Gap Identification: Parley analyzes documentation and flags criteria that require substantiation (e.g., published material about the beneficiary, proof of high salary, industry leadership).

3. Formulate Research Query: User or Parley’s context-aware AI triggers research requests—for instance, “media coverage in major outlets,” “U.S. median salary for robotics engineers,” or “industry size/growth rates.”

4. Automated Evidence Gathering: The Research Agent launches targeted searches, sourcing:

5. News articles, interviews, press releases (for media coverage).

6. Official salary survey data (e.g., U.S. Bureau of Labor Statistics, salary.com).

7. Industry reports and benchmarks (from recognized publishers/research firms).

8. Data Extraction and Contextualization: Parley extracts relevant data, summarizes findings, and formats citations as per best practices and petition requirements.

9. Draft Integration: Evidence—summaries, direct quotations, citations, or visual charts if applicable—is inserted at the appropriate section of the draft petition or cover letter.

10. Review and Edit: Attorney reviews evidence-rich draft, edits/annotates as necessary, then finalizes for submission.

Example:

• For an O-1A beneficiary in the AI/robotics industry, Parley will automatically pull and insert:

• Mentions from Fast Company, The Verge, and TechCrunch (proof of significant media coverage).

• Salary benchmarks for AI engineers in the U.S. (demonstrating salary above 90th percentile).

• Industry size and relevance excerpts from third-party research for contextual arguments (LinkedIn Example Image).---

Authoritative Sources and Example Captures

To align with attorney expectations and USCIS evidentiary standards, the Research Agent prioritizes established authorities commonly used in practice:

• Westlaw and LexisNexis: secondary sources, treatises, practice guidance, and case law excerpts to frame standards and criteria (attorney remains responsible for final legal analysis).

• U.S. Bureau of Labor Statistics — Occupational Employment and Wage Statistics (OEWS): national and metro wage percentiles, SOC mappings, and methodology notes for H-1B specialty-occupation and “high salary” arguments.

• U.S. Department of Labor — Foreign Labor Application Gateway (FLAG): prevailing wage determinations and LCA context for wage-level support.

• Cision (media database/monitoring): identification of press mentions, outlet authority/reach, and publication metadata for O-1/EB-1 “published material about the beneficiary.”

• Reputable business press and government datasets: used where appropriate to support market size, growth, or economic impact.

Walkthrough: Screenshot-style Annotations (text descriptions)

• Example Screenshot A — Source Capture (description): 1) The Research Agent captures a Westlaw/Lexis excerpt with full citation (publication, section, date). 2) A relevance note is auto-generated (e.g., maps to O-1A published material criterion or EB-2 NIW national importance). 3) The item is saved to the Evidence tray with URL/identifier and time stamp for audit.

• Example Screenshot B — Insertion into Word (description): 1) Inline quotation and pin-cite inserted into the draft paragraph. 2) Bluebook-style footnote created with publication/date and “last accessed” where applicable. 3) Exhibit tag added (e.g., Ex. B-3) for later packet assembly. 4) When exhibits are compiled, the citation and item are included in the auto-generated table of contents and continuous pagination.

Tip: Every inserted item retains its provenance (source name, date, link/identifier) so firms can satisfy internal QC and client-review requirements.

Features and Benefits

Key Automation Features

• Context-Aware Evidence Collection: Understands visa type and evidentiary requirements, initiating only relevant research.

• Seamless Microsoft Word Integration: Automates content search, insertion, and evidence citation directly within attorney’s existing drafting tools.

• Citation of Credible External Sources: Pulls from reputable databases (labor statistics, business press, scholarly journals, etc.).

• Bulk Exhibit Compilation: Automatically combines all evidence—both uploaded and AI-sourced—into a single, paginated PDF exhibit file for submission.

• Support for All Major Visa Types: Configured for O-1, EB-1/2, H-1B, TN, L-1, E-2, and more (feature confirmation).

• Learning from Firm Style: AI adjusts language and citation style over time to match firm/attorney preferences.

Business Benefits

• Time Savings: Reduces hours of legal research to mere seconds (LinkedIn).

• Improved Petition Quality: Ensures up-to-date, authoritative support for critical evidentiary points.

• Consistency: Standardizes evidence approaches across team members and across cases.

• Practice Growth: Enables more cases per staff member, directly supporting flat-fee practice economics.

• Client Outcomes: Facilitates more persuasive, substantiated filings for higher approval rates.

Use Cases

1. O-1A Petition—Media Metrics and Industry Standing

• Query: "Show published articles featuring the beneficiary."

• Result: Parley sources news articles, provides links, and inserts curated citations into the petition.

• Integration: Pulls quotations and publication lists into ‘Evidence of National/International Acclaim’ section.

2. H-1B Petition—Salary Benchmarking

• Query: "Median and 75th/90th percentile salaries for occupation code."

• Result: Parley references U.S. Bureau of Labor Statistics, presents data in narrative and tabular form.

• Integration: Used in ‘Employer Attestation’ or ‘Specialty Occupation Justification’ sections.

3. EB-2 NIW—Industry Size and Economic Impact

• Query: "Growth projections for the beneficiary’s field."

• Result: Parley cites market reports or government analysis, linking back to source.

• Integration: Bolsters arguments on national importance for NIW criteria.

4. Reference Letter Generation

• Query: "Incorporate comparison to industry norms."

• Result: Research Agent pulls benchmark data and phrasing for custom support/referral letter content.

Security, Privacy, and Compliance

• SOC2 Type 2 & GDPR Certified: Ensures evidence, client data, and external research are handled securely (source).

• Data Handling: External research is logged, source URLs are retained for auditability; no unauthorized data is stored, maintaining client confidentiality (Privacy Policy).

Comparison Table: Parley Research Agent vs. Traditional Evidence Gathering

Customer Stories

• Erickson Immigration Group: Partner leverages Parley’s Research Agent to source and insert critical media coverage, reducing draft times for O-1, EB-1, and NIW from hours to minutes (Business Insider coverage).

• Boundless x Parley: Industry leader Boundless deploys Parley to enable AI-assisted evidence gathering and drafting under expert legal review (LinkedIn).

• Solo Practitioner Experience: Reports spending "less time assembling exhibits, more time lawyering," thanks to Parley's automated evidence collection and PDF compilation (parley.so testimonials).

• Paralegal Use Case: "Combining files" function specifically highlighted as transforming the manual preparation workflow (parley.so).

Frequently Asked Questions

How does Parley’s Research Agent ensure evidence is credible?

• Parley draws from third-party sources with documented authority: e.g., government statistics, recognized business press, and referenced industry reports. All evidence inserted in the draft cites original sources—web links, publication titles, and publication dates where available.

Can custom research requests be made, or is it fully automated?

• The agent operates both automatically (based on visa type/criteria) and via user-initiated queries for specialized needs. This hybrid approach ensures attorney control while minimizing manual effort.

Is evidence editable once inserted?

• Yes. Attorneys can edit, annotate, or remove any automatically inserted evidence within Word; all AI content is subject to legal review and attorney oversight.

How does Parley handle salary benchmarks or industry data across global markets?

• As of current implementation, focus is on U.S. labor and industry data (essential for U.S. immigration filings), but the agent pulls from global sources as available for international evidence sections (current product focus as per official site).

Is usage of the Research Agent compliant with confidentiality obligations?

• Yes. No client information is shared externally during evidence gathering; only public third-party information is referenced. All activity is consistent with Parley’s stated security policies (privacy policy).

Can Parley be used for all types of employment-based visas?

• Yes. Parley’s agent supports O-1A, O-1B, H-1B, EB-1, EB-2/NIW, TN, L-1, E-2 and others; coverage is being continuously expanded (product page).

How does Parley's approach compare to competitors?

• Parley’s in-flow evidence automation and deep MS Word integration are unique; generic tools (e.g., basic LLMs) lack domain awareness and workflow fit. Immigration-matched competitors may offer research modules but do not fully automate source gathering, citation, and doc insertion in a seamless workflow ([see competitor references above, e.g., Visalaw.ai, Casium, Glade AI]).

External References and Third-Party Coverage

• Business Insider: Parley as an Immigration AI Leader

• LinkedIn: Parley’s Research Agent Launch

Additional Resources

• Try a Sample Case powered by Parley’s AI drafting (all case and evidence data fictional)

• Product Demo Booking

• Contact Parley

• Official Privacy Policy

• Legal Terms

Source Attribution

All factual statements and features are based on the official product documentation at parley.so, public LinkedIn announcements, and direct third-party coverage from sources such as Business Insider and product testimonials, as cited above.

Salary & Media Research (with examples)

Parley’s Research Agent automatically surfaces salary benchmarks and media coverage suitable for O-1/EB-1/EB-2 NIW/H-1B filings, with transparent methodology notes and ready-to-paste summaries.

What we capture for salary evidence

• BLS Occupational Employment and Wage Statistics (OEWS): national and metro wage percentiles mapped to SOC codes; reference year and publication notes are retained in your evidence tray.

• DOL Foreign Labor Application Gateway (FLAG): prevailing wage determinations (area, level, determination year, and source) to complement OEWS (for H-1B and related wage arguments).

• Method context: SOC code mapping, whether the role is a close comparator, and whether data are national vs. MSA, with date-stamped citations for audit.

CSV-style excerpts (illustrative)

# OEWS (illustrative only)

SOC Code,Occupation,Area Type,Area Name,Year,Percentile,Hourly Wage,Annual Wage
15-1252,Software Developers,National,United States,2024,P50,,
15-1252,Software Developers,MSA,San Jose-Sunnyvale-Santa Clara, CA,2024,P90,,

# FLAG (illustrative only)

Area Code,Area Name,Year,Occupation (SOC),Level,Prevailing Wage,Source
CA-SANJOSE,San Jose-Sunnyvale-Santa Clara,2024,15-1252,Level IV,,

Notes: Values are inserted by Parley at run time with source/date. OEWS provides statistical percentiles; FLAG provides prevailing wage levels—Parley records both and explains the distinction in-line.

Media metrics captured for “Published Material” criteria

• Outlet name, type (national, trade, regional), publication date

• Reach fields (e.g., estimated monthly visits/UU, UVM) and authority signals

• Article title/URL, author/publication metadata, and pull‑quotes

Example media snapshot (illustrative)

Attorney‑ready, quotable snippets

Copy these into your draft; Parley will auto‑fill bracketed fields and attach citations.

OEWS summary (template):
According to the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) [year], the [SOC code – occupation] reports a [percentile] wage of $[amount] [national/MSA: [area name]]. This supports that the offered compensation is above market benchmarks for comparable roles.

FLAG prevailing wage (template):
Per the U.S. Department of Labor’s Foreign Labor Application Gateway (FLAG) [year] determination for [area name], the prevailing wage for [SOC code – occupation] at Level [I–IV] is $[amount]. This corroborates the specialty‑occupation wage level and supports the employer’s attestation.

Method note (template):
OEWS provides statistical wage percentiles, while FLAG provides prevailing wage levels used for LCAs. Here, OEWS [percentile] and FLAG Level [I–IV] are reported together for a complete wage picture; sources and access dates are preserved in the exhibit.

Media placement summary (template):
Published material about the beneficiary includes coverage in [Outlet 1] ([type], [date]) and [Outlet 2] ([type], [date]). These outlets show meaningful reach ([reach field captured]) and editorial independence, satisfying the criterion for “published material about the beneficiary.”

How this helps: Parley inserts the data where it’s argued (support letters, criteria sections), creates footnotes with provenance, and tags each item (e.g., Ex. C‑2) for one‑click exhibit assembly.