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Vulcan Technologies
Vulcan Technologies is an Austin, Texas company building AI agents for legal, regulatory and government work. Its legal product, Justinian, is an agent that plans research, reads a knowledge graph of American law and policy, and drafts memos, redlines, rule text, comment responses and citation check reports with the sources attached. The vendor puts its source collection at about 157 billion records across 141 source families, from federal and state statutes and regulations to court records and a citation graph.
Justinian runs on the web, in desktop apps, in Slack and Microsoft Teams and by email, and since September 2026 includes Vulcan Office, a built in editor for documents, spreadsheets and slides. Government customers use it for regulatory review, rule drafting, legislative tracking and permitting; its public deployment list names the EPA Office of Inspector General and statewide deployments in Louisiana and Arkansas. A second product, Trajan, helps citizens and businesses complete permits and applications on government websites.
The federal deployment, VulcanGov, runs in AWS GovCloud (US) and is designated FedRAMP Ready. The company announced a $10.9 million seed round in October 2025, with General Catalyst and Y Combinator among its backers.
Capability grades
All 15 axes, graded from public sources on the date shown. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
The AI is the product. Justinian is sold as an agent that plans a research path, reads a knowledge graph of American law and policy, follows citations forward and backward, and drafts the memo, redline, comment response or cite check report, running as many parallel copies as a task needs, one per state for a 50 state survey. The source collection underneath has value of its own, but the vendor does not sell it as a search database; every surface presents it as what the agent reads.
The September 2026 release adds a built in office suite in which the agent fills spreadsheets and drafts documents and slides alongside the user.
Citation Accuracy and Hallucination Disclosure
Whether the vendor publishes measured accuracy on citations and assertions, grounds output to primary sources, and says plainly what its system does when it does not know. Legal has a documented public record of fabricated citations reaching filed briefs, so an untested claim of accuracy is not evidence.
Grounding is real and described, and accuracy has not been measured in public. The vendor says every claim is tied to the source passages Justinian read and that the agent follows the citation graph rather than treating authorities as isolated search hits. Release notes describe vector search tuned for legal text across all corpora, and exported documents carry clickable links from each regulation to its enabling statute, so a reader can open the authority behind a statement.
What is missing is measurement. No accuracy figure, error rate, test set or independent evaluation is published, and nothing names the failure modes a reviewer should watch for, which matters for a product whose output is drafted rule text and memos that a principal or a court will read.
Autonomy and Oversight Model
What the system decides on its own, what a lawyer must approve, and whether the vendor documents where the review point sits. A tool that drafts under review and a tool that files without one are different products and different risks.
A real control structure is described, without saying what the agent does on its own. Each agent run is tied to the user, workspace and task that authorized it, and tool access is scoped to the matter or agency environment and the class of action. High impact actions such as a filing, an outbound message, a decision or a record update can stop for human review, and elsewhere the vendor says humans approve sensitive actions.
Nothing says which actions always stop for approval and which only can. The agent also builds and deploys applications and runs recurring briefings inside the customer's environment, with no review step described.
Operational and Outcome Evidence
Named, dated evidence that the product works in production at real firms or legal departments. Case studies with figures and identified customers count. Unattributed testimonials and launch announcements do not.
Named deployments come in quantity, with no measured outcome that belongs to the product. The public deployment list names the EPA Office of Inspector General, statewide deployments across 20 Louisiana and 16 Arkansas departments and offices, and state offices such as the Virginia Office of Regulatory Management and the North Carolina General Assembly. The Virginia work is documented outside the vendor: a July 2025 executive order directed agencies to respond to AI generated analysis of their regulations, and trade press reported a three month pilot with Vulcan that summer.
The 26.8 percent reduction in Virginia's regulatory requirements often reported alongside that pilot was achieved before it began, and a later case study says the pilot's results are hard to separate from the wider effort. No law firm or corporate legal customer is named.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
Substantive commitments are published, on policy pages rather than in any agreement. The security page puts each deployment in its own boundary, says customer data is never commingled across tenants, and states that privileged matter material, citizen records and government material still under deliberation never leave the boundary. With no agreement published, none of this is yet a contract term. For the commercial deployment a law firm would buy, nothing names the model provider or says what it may retain.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
Nothing published addresses the advice line. No terms of service or usage policy exists on the site, and no page says the product is not legal advice, who may use it, or that a lawyer must review what it produces. The vendor's pages describe Justinian as advising on law and policy and sell it to policy teams, trade associations and startups as well as lawyers; the startup page offers launch risk memos and regulatory diligence to small teams that may have no counsel.
AI Governance and Bias Disclosure
Published governance over model behavior: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
No governance position for the AI is published. The security and FedRAMP pages are detailed about controls, monitoring, identity and encryption, and none of it concerns the models: nothing names who inside the company is accountable for AI output, what is tested before a release, or how uneven results across jurisdictions, agencies or populations are checked. That gap has weight here, because the product drafts rule text and regulatory reduction recommendations for governments and reviews permit applications, where an error or a skew falls on the public rather than only on the customer.
AI Safety and Data Stewardship
Retention, deletion, access control, and what happens to prompts and documents after they are processed. Whether the vendor states its subprocessors and its incident practice, or leaves the buyer to assume.
Most of the ground is covered on published pages, without a subprocessor list or incident practice. Retention is set by the customer, and public pages take requests to delete data or an account. Access runs through Okta single sign on with multifactor authentication and least privilege by role. Encryption uses FIPS 140-2 validated cryptography in transit and at rest with keys rotated annually, and the federal boundary is monitored with named tooling and a tamper evident audit log kept for several years.
No list of the companies that process customer data, and no statement of how and when customers are told of a security incident, is published.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
Nothing published says who bears the loss when the output is wrong. No terms of service, customer agreement, warranty or indemnity exists on the site, so no liability cap or allocation of risk can be read before signing. The question is live for this product: it drafts rule text, comment responses and permit review memos that a government acts on, and cite check reports a law firm relies on before filing.
Practice Systems Integration Depth
How deeply the product reaches into the systems legal work already lives in: document management such as iManage and NetDocuments, Word and Outlook, contract lifecycle management, matter management, e-billing, and court filing systems.
Integrations reach the channels users work in, one is documented, and none reaches the systems legal work is filed in. The Slack integration is described in useful detail. An admin installs it once through Slack's own authorization flow, each Slack user is matched to their Justinian account by email, files attached in a thread go in, and generated DOCX, PDF and spreadsheet files come back to the same thread. Justinian is also reachable in Microsoft Teams, by email and through desktop apps, and documents export as DOCX.
No document management, practice management or Word integration exists, and the September 2026 release goes the other way, adding an office suite inside the product so the work no longer has to live in Microsoft.
Deployment Model and Data Residency
Where the software runs and where the data sits. Multi tenant cloud, single tenant, private deployment, on premises, and whether region of residence is a published option or an enterprise conversation.
The federal deployment is specified exactly, and the commercial one is not. VulcanGov runs entirely in AWS GovCloud (US), in us-gov-east-1, with data stored and processed inside that boundary and model inference through AWS Bedrock in the same boundary. For commercial customers the vendor says each deployment runs in the customer's tenancy, data is kept in the US and private deployment is available, but it names no region and does not say where processing happens as distinct from storage.
Security Certifications and Trust Center
Independent attestation a buyer can pull without a sales call: SOC 2, ISO 27001, penetration test summaries, a trust center with current reports and named scope rather than a badge image.
Certifications are stated, and the evidence sits behind a request. The vendor states a SOC 2 audit covering security, availability and confidentiality and an ISO 27001 certified management system, with the report and certificate available on request; it does not say whether the SOC 2 report is Type 1 or Type 2, or give dates or an auditor. The federal deployment is designated FedRAMP Ready after assessment by an accredited third party assessment organization and is listed on the FedRAMP Marketplace, where it can be checked without a sales call. The control matrix, system security plan and a penetration test summary are offered in a security review.
Model Supply Chain Disclosure
Which models sit underneath, whose they are, where they run, and whether the vendor commits to telling customers when that changes. A legal buyer inherits every dependency it cannot see.
The models underneath are not named. Inference for the federal deployment runs on AWS Bedrock, which says where the models run but not which models or whose. The Slack integration accepts flags to choose a model and a provider, so more than one sits behind the product, and none is named anywhere on the site. Nothing commits to telling a customer when the models change.
Commercial Transparency
Whether a buyer can learn what this costs without entering a sales process: published rates, the unit being charged, what sits behind an enterprise tier, and what implementation adds.
No pricing is published at any level. There is no pricing page, no tier names and no unit of charge; the route to a price is a briefing request. The only public figure comes from trade press, where the chief executive put the Virginia pilot at $150,000 for three months, which is one government contract rather than a published price.
Firm and Practice Coverage
Who the product is actually built for. AmLaw, midlaw, small firm and solo, in house departments, government and courts, and which practice areas are supported rather than merely claimed.
Who the product serves is described with substance, and the boundaries are left open. Government coverage is mapped by function across agencies, executive offices and legislative counsel, from regulatory review and rule drafting to legislative tracking, audit and permitting. Commercial coverage has its own pages for six kinds of buyer, among them law firms, corporate legal teams and startups, each listing the work it supports.
The sources page states jurisdictional scope in detail: 51 jurisdictions, every municipal code, and local research in more than 40 cities and counties. No page states which courts, practice areas or kinds of matter the product should not be relied on for.
4 public documents
The public pages on file for Vulcan Technologies, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.
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vulcan.ai/security4 signals
Client Data in Training, Prompt and Output Retention, Third Party Request and Subpoena Notice and 1 more
Read Sep 27, 2026
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vulcan.ai/commercial3 signals
Ethical Walls and Matter Segregation, Refusal and Uncertainty Behavior, Billing and Fee Posture
Read Sep 27, 2026
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vulcan.ai/commercial/law-firms3 signals
Good Law Verification, Bar Guidance Alignment, Court Disclosure Support
Read Sep 27, 2026
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vulcan.ai/justinian/corpus1 signal
Primary Law Corpus Provenance
Read Sep 27, 2026
Legal Signals
What each signal meansA signal records what public sources say on the date shown. It is not a grade and it is not a recommendation. Where a signal reads Not addressed, it means the index did not locate the material in public sources on that date, which is a statement about disclosure rather than about the product.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
A public policy or trust page states no training on customer content, with no matching term located in the published agreement.
The security page states a position against training: customer documents and matter data are never used to train AI models. Since no agreement is published, the position is a policy statement rather than a contract term until one is signed. Checked 27 September 2026.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The customer controls the retention window, by product configuration or by contractual instruction, but zero retention is not stated as available.
The customer controls retention: the security page says the customer decides how long data is kept and that customer data is removed from the environment at termination. Nothing states whether retention can be set to zero, and prompts and outputs are not addressed separately from other customer data. Checked 27 September 2026.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Segregation is asserted in public materials with no published detail on how it is enforced.
Matter level scoping is asserted and not explained. The commercial page ties each agent run to the permissions that authorized it and limits tools to the matter, and the security page documents tenant isolation between customers. Nothing explains how access inside a firm is separated by matter, whether Justinian reads the permissions of a firm's document or matter system, or how a lawyer screened from a matter is kept from its files when the agent answers a question. Checked 27 September 2026.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
No located term or policy addresses third party requests for customer data.
No term or policy addresses what happens when a government, court or other third party demands customer data. The site publishes no terms of service, privacy policy or data processing addendum, and the security pages do not cover legal process. Checked the security, FedRAMP and support pages and the sitemap on 27 September 2026.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Sources are identified without stating the license or rights basis.
The source collection is catalogued family by family, without a rights basis. The sources page indexes 141 source families across 15 categories, each with its jurisdictional scope, document types and volume notes, from federal and state statutes, regulations, registers and court records to government datasets such as the DOJ Justice Manual and FEC campaign finance records. Recent entries show ingestion dates. Nothing says where court opinions and other primary law come from, or on what license or public domain basis each source is held. Checked 27 September 2026.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
The vendor computes and surfaces subsequent history itself, with the method described.
Justinian checks treatment itself rather than licensing a citator. The law firm page sells cite check reports that audit drafts for citation support, negative treatment and missing authority and answer which cases are still good law, and the sources page describes a citation graph of 5.37 billion records that the agent follows forward and backward. No commercial citator is named. Nothing says how a negative treatment is identified, whether editors review it, or how accurate it is. Checked 27 September 2026.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
The product exposes a confidence or grounding score without an explicit abstention path.
The product flags weak support rather than describing a refusal. The vendor says weak support is flagged on the claims Justinian makes, which tells a reviewer where to look. Nothing describes what Justinian does when it finds no support at all, whether it declines to answer or says so, and no published evaluation shows it. Checked 27 September 2026.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.
No court order, opinion or disciplinary record addressing fabricated or hallucinated citations produced by Justinian or Vulcan Technologies was located as of 27 September 2026.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
No located public material engages with bar or ethics guidance.
No published material engages with bar or ethics guidance on AI in legal work, in general terms or by name, although the product is sold to law firms and corporate counsel. The commercial, law firm, corporate counsel, security and product pages were checked on 27 September 2026.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
A usable record of AI assisted work exists with no published fee guidance.
A usable record of AI work exists, with no guidance on billing. Each output keeps its source passages, retrieved files, tool calls, generated files and approvals attached, and tool access follows the matter, so a firm can see what the agent did on a given piece of work. Nothing published addresses how that work should be billed or disclosed to a client. For the government, policy and corporate buyers most of the site addresses, no client fee is involved. Checked 27 September 2026.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
The material exists behind a sales conversation or an executed agreement.
Disclosure material exists behind a security review, not on the open site. The security page offers the SOC 2 report, the FedRAMP control matrix and system security plan, a penetration test summary, and an architecture and data flow review covering integrations and where data lives, all on request. No subprocessor or model provider list is published. Checked 27 September 2026.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Some elements of the record are available, short of a document level export.
Part of the record a court certification needs is kept with each output. The law firm page describes packaging the reasoning path so a reviewer can see what was searched, what controlled and what was rejected, and the vendor says human approvals stay attached to the work. Nothing says the record names the model used, and no export of that record, template or guidance on court disclosure rules is published. Checked 27 September 2026.