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We transform real ones.
We leverage bleeding-edge AI models and years of experience. See how businesses are optimizing critical legacy processes and transforming the value they create.
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Inbound counterparty paper in. Severity-rated clause cards, a triage row, and a redline shortlist out.
Every NDA, vendor MSA, and supplier addendum triaged before it hits an attorney's queue.
First-pass review before the queue: an orchestrator walks every contract page by page, a vision sub-agent isolates each clause with tight bounding boxes, and a per-clause pass rates it against the team's playbook — green, yellow, orange, red — with a plain-English explanation and a redline ask. The reviewing attorney opens the document already triaged: severity counts, key concerns linked to section numbers, and a single-line bottom line about whether the paper is signable as drafted.
- A vendor sends back the MSA with fourteen redlines. The process reads each marked clause, classifies it as positional or material, and tells the reviewing attorney which two of the fourteen actually shift risk and which twelve are stylistic. The redline review becomes a five-minute scan instead of a ninety-minute compare.
- The counterparty's limitation-of-liability cap reads at six times annual fees on the surface. The per-clause pass detects an embedded carve-out in section 11.4 that excepts IP indemnity from the cap entirely, flags it red, and links it to the Limitation of Liability card. Three out of four reviewers would have missed it on a thirty-second scan.
- The team's playbook lives in the deal context. 'No fee-shifting; cap at 12× fees; arbitration in Ontario only; no broad IP assignments.' Every clause that touches one of those rules is rated against the playbook, not against a generic baseline. New reviewers ship the same opinion as the GC on day one.
Two agents coordinate your services and redact every document according to the rules.
Process FOI requests from intake to compliant redacted dossier
Two agents, two duties: one maps and tasks every record‑holding service for a FOI search, while the other permanently redacts restricted passages and logs the exact legal basis for each blackout.
- A request mentions "all communications related to the Riverside development, 2022–2023." The agent reads it and sends seven different briefs — one to Engineering, one to Legal, one to Planning, one to Procurement, two to Finance, one to the Mayor's Office — each scoped to the specific records and systems that department controls. The clerk didn't make a list. Nobody did.
- The requester appeals a redaction. The justification log already shows: page 4, paragraph 2, the phrase "personal home address," blacked out under section 17(1)(c) of the Act, applied on April 16 at 14:32. The municipality's position was documented before the appeal was filed.
Call recordings and CRM data in. A ranked breakdown of stall patterns, by rep and by quarter, out.
Find out why deals stall — across every rep, every quarter
Sales leadership wants to understand why deals over $100K are stalling at technical evaluation. The agent ingests 60 recorded calls from Gong and cross-references them with the pipeline export showing deal stage, ACV, and final outcome. It identifies the patterns: which objections appeared in deals that went dark vs. deals that closed, which talk-track moments correlated with positive stage progression, which technical questions the reps couldn't answer and whether they came up in every stalled deal. Coaching briefs are written per rep and logged in Salesforce against each rep's profile. Leadership gets the aggregate view posted to #sales-leadership in Slack before Monday's pipeline review.
- The analysis is built from both call content and deal outcome. A question that always comes up isn't a signal; a question that always comes up in deals that go dark is.
- Coaching briefs go into Salesforce against each rep's record. Sales managers don't forward a PDF — they open the rep's profile and see the brief alongside their pipeline.
Thirty recorded discovery calls in. A structured product brief with themes, quotes, and feature signal, out.
From 30 recorded calls to a structured product brief. Without anyone pressing play.
The product team runs 30 customer calls. Today, those recordings sit in a folder until someone finds time to listen. This agent processes every call, extracts quotes by theme, maps what customers are asking for against the current roadmap — and calls out the gaps no one planned to solve. The output lands directly in the product management tool as tagged, prioritized notes. PMs open their existing workflow and the research is already there, structured and actionable.
- 30 calls processed. Zero hours of listening. Every insight mapped against the actual roadmap — gaps the team didn’t know existed, surfaced before the next sprint planning.
- Open the product management tool on Monday morning and the research is already there. Tagged, prioritized, linked to source clips. Like a research team that works weekends.
Vendor proposals normalized and scored against criteria. Risk clauses surfaced.
Normalize, evaluate and pre-score multiple vendor proposals
An agent to read all proposals, normalizes pricing to a common unit — per seat per month, fully loaded — and builds a single comparison matrix covering capabilities, SLAs, and support tiers. It also flags risk terms buried in the fine print: auto-renewal clauses, liability caps, data ownership provisions. The procurement team adds relationship context. The recommendation brief lands in the team channel, ready for review.
- One vendor sent a 12-slide deck. Another sent an 80-page spec. A third sent a pricing sheet in an email. By morning, all five are normalized — per seat, per month, fully loaded — in a single matrix.
- Auto-renewal clauses. Liability caps. Data ownership terms buried on page 47. The fine print the team doesn’t always have time to read carefully? Flagged and summarized.
Turn RFPs turned into compliant proposals with proven language.
Turn a 800-page RFP into a drafted response with proven language pulled, content gaps marked, and compliance matrix built.
An 800-page RFP lands on a Friday. The AI reads every section, extracts every requirement, and checks each against past proposals and the knowledge base. Where a requirement matches something that’s been won before, the proven language is reused. Where it doesn’t, it flags the gap so writers focus where it matters. Forms are pre-filled, and response checklists are prepared to make sure nothing is missing. Before submission, using the team's contribution, the agent rebuilds the compliance matrix against the final draft to double-check that every requirement is addressed and nothing was lost in edits.
- A requirement the firm has won on before? The proven language is already in the draft. A requirement never seen before? It’s flagged so writers spend time where it matters — not on boilerplate.
- The compliance matrix isn’t a one-time check. It’s been rebuilt against the final draft, after all the edits, right before submission. Nothing slips through.
Competitor signals monitored continuously. Pricing changes, product launches, and positioning shifts summarized before every leadership meeting.
Know what your competitors are doing before your leadership meeting
A B2B software company tracks eight direct competitors. The agent monitors them across news, job boards, product changelogs, regulatory filings, and public forums. Every Monday it produces a categorized digest delivered to a shared Notion page before the leadership meeting. Job posting patterns get called out specifically — a burst of ML engineering hires or a newly opened VP of Partnerships role signals a strategic move weeks before any press release. Items are weighted by significance: a brand refresh gets one line, a new enterprise pricing tier with usage-based billing gets a full paragraph and a watch flag.
- Job postings tell the real story. A burst of ML engineering hires or a newly posted VP of Partnerships signals a strategic shift weeks before any press release.
- Not everything is worth your attention. A brand refresh gets one line. A new enterprise pricing tier with usage-based billing gets a full paragraph and a watch flag.
Applications come in. Each one is read, classified by type, code-checked, and queued before a permit officer touches it.
A week’s worth of permit applications reviewed, sorted, and code-checked before lunch.
A planning department receives 80–120 applications a week. The agent reads each one, cross-references the current building code, zoning ordinance, and project description, and sorts them: complete applications go to the approval queue with a summary; incomplete ones get a deficiency notice citing the exact code section and what’s missing. Reviewers start from a queue of actionable files, not a stack of paper.
- A new ordinance takes effect Tuesday. By Wednesday, every application is already reviewed against it. No one updated a checklist. No one sent a memo.
- Applicants who get a specific deficiency notice fix the right thing and resubmit once. The ones who get a vague rejection? Three resubmissions, two phone calls, and a complaint to the council.
A job description and an applicant pool in. A ranked shortlist with structured evaluation notes, out.
Automating an in-house recipe to pick promising candidates amongst applicants
Four hundred applications come in for a senior product role over ten days. The agent scores every submission against the job spec, the team's rubric, and the compensation band. Strong matches get a two-line summary of what stands out. Clear mismatches get a draft decline citing the specific gap — wrong seniority level, outside the comp range, missing a required domain. Career changers and non-traditional backgrounds get flagged for recruiter review with a note on what's strong and what's uncertain. Every application is scored on the same rubric, regardless of format or background. The hiring manager starts from a ranked shortlist. Every applicant receives a message, which is rare enough to strengthen the business's reputation as a desirable employer.
- Résumés with gaps, non-linear careers, and unconventional titles get scored on the same rubric as conventional ones. The agent doesn't penalize format.
- Draft declines cite the specific criteria not met — experience level, missing certification, outside the comp range. Candidates get a real answer, and the team doesn't spend a week composing the same email 300 times.
Take a complex vendor contract. Get it highlighted, with reasoning and warnings.
Vendor contracts redlining
A cloud infrastructure vendor sends over their standard MSA. Sixty-two pages. The agent reads it against the company's contracting playbook and flags every deviation: indemnification clauses that exceed the accepted liability threshold, data processing terms that conflict with the privacy policy, SLA commitments in the statement of work that didn't make it into the contract. It generates a redline draft substituting preferred clause language wherever a vendor term is unacceptable. Legal reviews the exceptions and sends the markup in one pass.
- Indemnification language that looks standard rarely is. The agent compares each clause against your accepted risk thresholds and flags anything that shifts material liability onto your business.
- The redline is built from your own clause library. Where a vendor term is unacceptable, the agent substitutes your preferred language. Your legal team edits the exceptions, not the boilerplate.
A grant opportunity and your program data in. A polished, criteria-aligned application, out.
Strengthen grant applications and increase your win rate
A nonprofit applies for a federal workforce development grant. The agent reads the 40-page guidelines, checks eligibility against every stated criteria, and starts drafting — pulling language from the organization's two previous funded applications and adapting it to this funder's priorities. It pre-fills the budget template to spec and tracks every required attachment against the full requirements list, including the ones buried in the appendix. The program team writes the impact narrative. The agent runs a completeness check before submission.
- The agent pulls from your strongest past applications — the ones that got funded — and adapts the language to the new funder's priorities. You're not starting from a blank page.
- Requirements buried on page 14 don't get missed. The attachment tracker cross-checks the grant's full requirements list against what's actually in the package.
Offer accepted. Access provisioned, forms completed, equipment ordered, training queued — before day one.
Day one. Access provisioned, forms filled, training queued. HR didn’t coordinate any of it.
A new engineer joins Monday. The agent builds the full onboarding packet from the handbook, benefits catalog, IT checklist, and org chart — pre-populating every form and generating a role-specific setup list: source control access, VPN credentials, dev environment, security training. HR assigns the buddy. The agent tracks every outstanding signature and overdue item daily until the file is complete.
- Engineering hire: source control access, VPN, dev environment, security training. Sales hire: CRM, phone line, demo environment. The setup list is built from the role — not pulled from a generic template.
- No one in HR chases signatures. Every outstanding item is flagged with who owns it, every day, until it’s done. Like a project manager who never forgets and never nags.
Invoice in. Matched against PO, contract, and policy. Clean ones approved. Flagged ones cite the exact clause.
Pre-process invoices. Identify potential duplicates. Flag problems with the relevant contract clauses.
The agent matches every invoice against the purchase order, service agreement, and expense policy before it reaches an approver. Clean matches auto-approve. Exceptions are routed to the finance system with the exact reason: not “flagged for review” — the specific policy clause and what it prohibits. The team opens a queue of decisions, not a pile of documents.
- Same vendor, same amount, same date range, different invoice number. That’s not an error — it’s a duplicate designed to get paid twice. The agent catches it at volume.
- Every flag comes with the policy citation. Not “flagged for review” — “Exceeds $500 meal limit per Policy 4.2.1.” Approvers make the call in seconds, not minutes.