From a real task to a repeatable system

What could Kijulo do in your workday?

Start with your role, not a feature list. These practical workflows turn scattered information and repeated decisions into systems you can run, review, and trust — every fact traced to its source, verified, and kept current.

Built for your practice

How a firm runs a whole practice on Kijulo

From the first document to the final decision — one evidence base where every fact is traced, verified, and reused. Here is the A-to-Z for the three practices Kijulo is built for.

Legal & Compliance

Take a matter from intake to audit-ready — the same standard every time

A legal or compliance team runs its entire review practice on Kijulo. Every clause links to its source, every finding is verified and dated, and the whole matter stays defensible.

1
Intake & structure

Contracts, matters, and obligations land in linked tables — each file kept with its source and version.
2
Clause extraction

The agent extracts key clauses and links each to the exact passage. No finding exists without its source.
3
Standard review

Every file runs through a repeatable compliance protocol; deviations from your standard are flagged, verified, and dated.
4
Change tracking

Revisions are compared to isolate material changes; clauses whose source changed are flagged stale for re-check.
5
Audit trail

Every finding, who approved it, and when — an audit-ready record you can defend to a regulator or a court.

PE, Financial & M&A

Run a deal from first look to exit — on one evidence base

An investment or M&A team runs the full deal lifecycle on Kijulo. Verified facts are separated from management claims, every figure is traced, and the reasoning survives to inform the next deal.

1
Source & screen

Deal flow and market data land as structured rows; the agent screens against your thesis and flags fit — every figure linked to its origin.
2
Diligence

Ingest the CIM, management deck, and diligence reports; the agent separates verified facts from management claims and surfaces contradictions across documents.
3
Investment committee

A live evidence pack — thesis pillars, risks, and assumptions, each with provenance and a confidence level. The IC debates real numbers, not slides.
4
Decision record

The decision, its rationale, and the entry assumptions are preserved — so later you can tell bad information from bad execution.
5
Portfolio monitoring

Monthly packs flow in; the agent proposes KPI updates and flags deterioration against plan — always through a review queue.

Insurance & Claims

Review a claim from intake to decision — with the evidence, not a black box

A claims team runs its integrity review on Kijulo. Each claim is scored by corroboration across transactions, and the contradictions are laid out for a human to decide.

1
Intake

Policies, claims, and provider transactions land in one linked graph — each record kept with its source.
2
Cross-check

The agent cross-references each claim against the claimant's history, the provider's other transactions, and the policy terms.
3
Score

Each claim gets a confidence score from corroboration across sources — with the evidence, not a black-box number.
4
Human review

Low-confidence and contradictory claims route to a reviewer with every source laid out; nothing is auto-decided.
5
Decision record

The decision and its evidence are preserved — a defensible, auditable trail on every claim.

Explore by domain

Showing 13 workflows

Investment or M&A analyst

Setup: 1.5 hours · Advanced

Build a verifiable, evidence-backed underwriting record

Bring deal flow, financials, and research together; separate verified facts from management claims; score each opportunity consistently; and keep every datapoint linked to its source for the IC.

What you get

A transparent deal funnel where every figure is traced to its source, verified or flagged, and kept current — decision-ready comparisons the investment committee can trust.

Explore workflow

Worked example

A management deck claims 2025 EBITDA of €43m. The agent cross-checks it against the audited accounts, the CIM, and the latest board pack — and flags a €5m gap between 'adjusted' and reported EBITDA, tracing each figure to its exact page. It separates the verified €38m from the €43m management claim, marks the adjustment unverified, and drafts the IC note with both numbers and their sources. Now the deal team argues over a real figure, not a slide.

How the workflow runs

1Import targets and define the fund or buyer criteria you care about.Create structured data →
2Enrich financial and market data from APIs and source documents, attaching a source and retrieval date to every figure.Connect an external API →Search and synthesize documents →
3Separate verified facts from management claims, score every target with weighted Fit Plan criteria, and inspect the breakdown.Create a Fit Plan →
4Run a due-diligence protocol and ask the agent to draft a sourced comparison memo — every claim linked to its evidence.Create a Protocol →Start an agent conversation →

Built with

Structured dataFit PlansDocument retrievalProtocolsDiff View

Lawyer or compliance analyst

Setup: 1 hour · Intermediate

Review every contract against a verifiable standard

Search a contract library, extract key clauses with a link to the exact source, compare versions, and walk every file through a repeatable checklist — so every finding is traceable, not asserted.

What you get

Faster first-pass review where every finding links back to the clause it came from, verified against the current version — a consistent, auditable standard across matters.

Explore workflow

Worked example

Across 60 vendor contracts, the agent extracts every limitation-of-liability clause and links each to the exact page it came from. It finds three contracts whose liability cap was quietly lowered in the latest amendment, flags them against your standard, and records each finding verified and dated. A first pass that used to take a day surfaces the three contracts that actually matter — every one traceable back to the clause.

How the workflow runs

1Add contracts and their metadata to a searchable workspace, each file tracked to its source and version.Search and synthesize documents →Create structured data →
2Ask the agent to find and summarize clauses, with a link back to the exact passage in the source.Start an agent conversation →
3Compare revisions side by side to isolate material changes, and flag clauses whose source has changed.Build a useful view →
4Run a reusable review protocol and record findings against the contract, marked verified and dated.Create a Protocol →

Built with

Document retrievalAgent sessionsDiff ViewProtocolsSource Trace

INS

Insurance claims reviewer

Setup: 1.5 hours · Advanced

Score claim data by cross-checking every transaction

Bring policies, claims, and provider transactions into one linked graph, then let an agentic reviewer score each claim's reliability by corroborating it across the claimant's history, the provider's other transactions, and the policy terms — flagging contradictions with the evidence behind them.

What you get

A confidence score and a contradiction trail on every claim, each linked to its source — so reviewers spend time on the claims that don't add up, not on re-checking the ones that do.

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Worked example

A motor claim comes in at £14,200. The agent cross-checks it against the claimant's three prior claims, the repair shop's invoices across 40 other claims, and the policy's declared vehicle value — and finds the repair estimate is 38% above the shop's median for that part, while the incident date overlaps an earlier total-loss claim. It scores the claim low-confidence, cites every source, and routes it to a human with the contradictions laid out. Nothing is auto-denied; the reviewer decides with the evidence in front of them.

How the workflow runs

1Bring policies, claims, and provider transactions into linked tables — each record kept with its source document.Create structured data →Import Excel or CSV data →
2Let the agent cross-reference every claim against the claimant's history, the provider's other transactions, and the policy terms.Create relationships between data →Compare subsets of your data →
3The agent scores each claim by how well it corroborates across sources and flags contradictions — with evidence, not a black-box number.Start an agent conversation →Identify clusters in your data →
4Low-confidence or contradictory claims route to a human reviewer with every source laid out; nothing is auto-decided.Create a Protocol →Review and approve agent changes →

Built with

Structured dataAgent sessionsRelationshipsProtocolsSource TraceDiff View

For your personal life

Setup: 15 min · Beginner

Build a second brain you can actually inspect

Keep notes in ordinary local files, organize the ideas that matter as structured data, and let an agent help you connect and retrieve them without locking your memory inside an app.

What you get

A private, searchable knowledge system where your notes stay portable and every useful connection remains understandable.

Explore workflow

How the workflow runs

1Point Kijulo at the folders where you already keep notes, journals, receipts, or research.Work with local files →
2Create lightweight structures for people, projects, ideas, books, or anything you want to track.Create structured data →
3Ask the agent to summarize new material and propose links to related notes for your approval.Start an agent conversation →Review and approve agent changes →
4Use saved views and natural-language questions to resurface useful information when you need it.Build a useful view →

Built with

Local filesStructured dataAgent sessionsRelationshipsSource Trace

Learner and curious mind

Setup: 15 min · Beginner

Turn a one-hour YouTube video into a five-minute read

Save a video once, then let a repeatable workflow retrieve its transcript, remove the repetition, and preserve the ideas that are actually worth remembering.

What you get

A concise, source-linked brief you can read in five minutes, plus reusable ideas and insights stored in the right tables—not another video lost in a playlist.

Explore workflow

How the workflow runs

1Add the YouTube URL to a Videos table with its title, creator, topic, and viewing status.Create structured data →
2Run a workflow that retrieves and stores the complete transcript so the source remains available.Ingest a video, PDF, or document →Create a Workflow →
3Ask the agent to produce a concentrated summary with the main argument, key insights, useful examples, and actionable ideas.Start an agent conversation →
4Save the readable brief as a local file and propose structured Insight and Idea rows linked back to the video for your approval.Work with local files →Review and approve agent changes →

1Create simple structures for sources, notes, concepts, and categories.Create structured data →
2Give a file, article, or video to the agent for structured extraction.Ingest a video, PDF, or document →Start an agent conversation →
3Review proposed concepts and preserve the source behind every claim.Review and approve agent changes →
4Run a weekly workflow that finds unlinked ideas and suggests useful connections.Create a Workflow →Schedule recurring work →

Built with

Structured dataAgent sessionsWorkflowsSource Trace

DEV

Professional software developer

Setup: 30 min · Intermediate

Give coding agents durable project context

Keep architecture decisions, issues, proven commands, and project knowledge beside the code so each agent starts informed and every proposed change stays reviewable.

What you get

Less repeated explanation, safer agent-assisted changes, and project knowledge that compounds across coding sessions.

Explore workflow

How the workflow runs

1Connect the repository and keep its domain language, architecture decisions, and working conventions in local files.Work with local files →
2Structure features, bugs, decisions, and dependencies so agents can query the exact context they need.Create structured data →
3Record verified build, test, and deployment commands in the Command Book instead of rediscovering them.Record a proven command or runbook →
4Use workflows for repeatable review or release tasks and trace proposed changes back to the session that produced them.Create a Workflow →Review and approve agent changes →

Built with

Local filesStructured dataAgent sessionsCommand BookWorkflowsSource Trace

Data or IT operations manager

Setup: 1 hour · Intermediate

Make incident response repeatable and reviewable

Track incidents and services, attach proven runbooks, and let an agent gather the right context without hiding what it did.

What you get

A live incident board, reusable response procedures, and better post-incident learning.

Explore workflow

How the workflow runs

1Structure incidents, affected services, owners, severity, and status.Create structured data →
2Attach a tested runbook to each incident category.Record a proven command or runbook →
3Let the agent inspect approved logs and execute the relevant diagnostic steps.Start an agent conversation →Work with local files →
4Record the resolution and review recurring causes across past incidents.Build a useful view →

Built with

Structured dataAgent sessionsWorkflowsSchedulesBoard View

Your workflow will be specific to you

Start with one repeated decision

Choose the task your team repeats most often. Structure the information once, add an agent where judgment helps, and keep approval where it matters.

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