Approved tools and data
Use only firm-approved systems, permissions and data categories.
Human-led. Attorney-supervised. AI-enabled.
How can I prepare a source-linked chronology and demand draft?
AI-assisted demand package preparation turns an approved record set into a draft timeline, bill register and exhibit list for human review. A remote paralegal checks dates, amounts and source references before an attorney uses the material. AI prepares a working draft. It does not decide causation, damages, case value or the demand amount.
Custom pricing. Scope and price confirmed in writing.
Match education to the work, then test the work
Legal support outsourcing should begin with role fit. Review the proposed specialist’s education, relevant experience, writing and practical work against the task. LL.B., LL.M., J.D. and paralegal training describe different pathways; they do not establish U.S. attorney licensure.
Use a synthetic exercise that requires source checks and handling an unclear answer. Agree the review owner and permissions before a person or tool receives access.
Explore education and vetting ↗The problem, in the firm’s words
A draft timeline reads clearly but contains an event with no page reference. A bill appears twice in the working total. Before the attorney can evaluate the case, someone must trace each entry back to the correct document.
What changes in the workflow?
The proposed build changes the preparation and review process. It is not a measured client result.
Before: an illustrative manual process
After: the proposed reviewed process
Before: disconnected preparation
- Disconnected record notes
- Repeated bill entries
- Broken exhibit references
- Unclear draft status
After: proposed reviewed process
- Linked chronology entries
- Checked bill register
- Reviewed exhibit manifest
- Attorney-ready draft packet
What we build, step by step
- Define the timeline fields and separate event date from record-entry date. Keep inconsistent dates as exceptions rather than selecting one automatically.
- Prepare a bill register with document references and duplicate flags. Use deterministic calculations for totals and keep adjustments visible.
- Assemble an approved demand template and exhibit manifest from reviewed entries. Mark draft content and provide the attorney with unresolved questions alongside the packet.
Start with the software your firm already owns
We first check your current plan, permissions and supported interfaces. A missing feature or API entitlement becomes a scope decision, not an assumed integration. Tesseract may supply OCR and an approved Ollama installation may host a separately licensed model. Model choice, context limits and source-link checks must be tested on the intended document types.
Tesseract OCR product and license referenceOllama product and license reference
What a person checks, and how
The paralegal verifies each event, bill line and exhibit reference against the source. They check chronology order without assuming that time order proves causation. Unsupported statements are removed or flagged before attorney review.
What stays with your attorneys
Medical causation, legal theory, valuation, negotiation position, demand amount, legal conclusions and final signature.
ABA Formal Opinion 512: generative AI guidanceABA Model Rule 5.3: nonlawyer assistance
How we test the proposed workflow
Use a fictional packet with an amended report, duplicate invoice and conflicting event dates. Acceptance requires visible exceptions, source links and a total that can be reproduced from reviewed inputs.
The acceptance record identifies the source version, reviewer, expected result and unresolved exceptions. These are proposed synthetic tests, not a claim about a completed client deployment.
Timeline and custom pricing
We scope the records, systems, review steps and acceptance tests before estimating timing. Fixed-scope projects. Pricing confirmed in writing before work starts. Hosting, model usage, software plans and support are identified separately where applicable.
Run it yourself or have us run it
A Build Sprint delivers the agreed workflow and a documented handoff to your team. A Managed AI Operator engagement adds a trained person to run review queues, check every output and escalate exceptions. The build and human seat are separate scope items.
A person remains accountable
Six controls for every proposed AI workflow
Drafts with named reviewers
Label every AI output as a draft and route it to a named human reviewer.
Traceable extracted facts
Keep a source link or document/page reference for every extracted fact.
Visible exceptions
Log missing evidence, conflicting inputs and failed steps. Never silently fill gaps.
Attorney approval before sending
AI never makes legal decisions or gives advice. Nothing is sent to a client, court or opposing party without attorney approval.
SOC 2 Type II scope review
Remote Legal Team LLC states SOC 2 Type II security. Confirm report scope, period and covered services during diligence; it does not certify every proposed tool or make a workflow automatically compliant.
Questions about this workflow
Does this replace my existing legal software?
No. We first assess the firm-approved tools and interfaces you already have. A separate component is proposed only when its purpose, license, data access and cost are agreed.
Who approves the legal work?
Medical causation, legal theory, valuation, negotiation position, demand amount, legal conclusions and final signature. AI output remains a draft and all legal work stays under attorney direction and approval.
How is this AI automation project priced?
Pricing is custom and confirmed in writing against the agreed scope. We identify build work, software or hosting costs and any ongoing human operator separately.
Sources and product references
Checked October 13, 2026. Product access depends on the current account, plan and configuration.
Related legal support
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Describe the workflow, approved systems, expected draft output and review owner. We will confirm the scope and custom pricing in writing before work starts.
We’ll discuss relevant education and experience, workload, coverage, commercial terms and your review process.
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Discuss ai chronology & demand preparation support, your team’s workload and the next steps for your organization.