BUILD
Understand
& structure
Zeldan Labs · AI Agents
We build things that pay attention.
Specialized AI agents for repetitive enterprise work between your people and your systems — reading, structuring, monitoring, ranking and escalating what needs a human.
FIX
Detect gaps
& resolve
VALIDATE
Check output
& explain
DEPLOY
Escalate
& act
Human-in-the-loop
AI handles repetitive work. People stay in control.
Explainable outputs
Important decisions arrive with context and evidence.
Workflow-specific
Built around real processes, not generic automation.
Integrated by design
Connects with the data, tools and systems you already use.
From products to enterprise systems
Four launch agents. One architecture built to extend.
Our first agents productize workflows in hiring and data operations. They are the starting point, not the boundary: the same agent architecture can be designed around a bounded workflow inside your enterprise — using your data, systems, rules and human approval points.
Four agents. One operating pattern.
Working product patterns we can demonstrate, refine and expand.
Enterprise agent engineeringBuilt around your workflow
CUSTOM / 05+
Your workflow can become the next agent.
We design focused agent systems around repetitive enterprise work — connecting models with business rules, existing tools, structured data and explicit human checkpoints.
Data & EngineeringFinanceRevenue OpsCustomer OpsCompliancePeople Ops+ Your workflow
01Your systems
→02Zeldan Labs agent layer
→03Human checkpoint
→04Action + audit
Start with one repetitive workflow where the inputs, rules and exceptions are clear enough to test.
See enterprise workflows →Launch agents
Meet the first four.
These are the first workflows we are building, available in early access. Each agent stays narrow, produces visible outputs, and demonstrates the operating pattern we use when designing larger enterprise agent systems.
01 / PROFILE READEREarly access
Turn messy CVs into decision-ready data.
Reads inbound candidate profiles, extracts experience and skills, and creates a consistent record that recruiters can search, review and compare without manually re-reading every document.
02 / REQUIREMENT PARSEREarly access
Give it the brief exactly as the client sent it.
Converts incomplete emails and conversations into a structured hiring requirement, then highlights what is missing before a recruiter starts sourcing against assumptions.
03 / PIPELINE WATCHEarly access
See the change before the failure.
Watches data pipelines for schema drift and high-risk changes, then explains likely downstream impact so teams can act before a scheduled job turns into an incident.
04 / SHORTLIST DRAFTEREarly access
Rank candidates with the reasoning attached.
Compares screened candidates against a structured requirement and drafts a shortlist that a recruiter can inspect, override and send — without hiding why somebody ranked above somebody else.
Live agent
Don't read about it. Run it.
This browser demo keeps the logic local. Paste a rough role requirement and the interface will show how a requirement parser can structure the information and identify gaps.
Input / client brief
Agent trace / structured result
Waiting for input…
Enterprise workflows
Same operating model. Different business function.
The first agents focus on hiring and data operations. The same bounded architecture can be adapted to other enterprise workflows when the work has repeatable inputs, clear rules, exceptions and a defined point where a person should remain in control.
01Data & engineering
Keep technical operations ahead of the failure.
Monitor pipelines, inspect data quality, investigate incidents, interpret metadata and prepare engineering actions.
02Revenue operations
Keep every opportunity moving.
Enrich records, detect stalled work, summarize account context and prepare the next action for review.
03Customer operations
Resolve repetitive requests with context intact.
Understand incoming cases, collect missing information, route exceptions and prepare grounded responses.
04Finance
Turn repetitive document work into review-ready decisions.
Read documents, reconcile fields, flag mismatches, assemble evidence and prepare approval queues.
05Compliance
Watch the conditions that should never be missed.
Monitor policy conditions, identify exceptions, assemble evidence and escalate consequential cases to people.
CUSTOMEnterprise agent
Bring us the workflow.
Your systems, your data, your business rules and your approval points — shaped into one clearly bounded agent system.
Design the first workflow →YOUR DATA→YOUR RULES→YOUR SYSTEMS→HUMAN APPROVAL→TRACEABLE ACTION
Design principles
Useful AI is mostly about what happens after the prompt.
We design agents around business boundaries: what they can read, what they can decide, what they must explain, and exactly where a person remains in control.
Decision boundaryHuman control remains visible
01
ReadDocuments, records, messages and events.
→
02
InterpretRules + models convert input into structure.
→
03
ExplainImportant outputs carry context and evidence.
→
04
EscalateConsequential actions route to a person.
Human checkpointReview required before external action
● CONTROLLED01
Narrow by designOne workflow, clearly bounded.
02
Visible outputsNo hidden black-box handoff.
03
Human checkpointsPeople retain consequential control.
04
Fits your stackWorks with existing systems.
Architecture
Built to sit between data, models and decisions.
The product experience is only the surface. Underneath, each implementation can combine deterministic logic, LLM reasoning, business rules, structured data and human review.
AzureDatabricksPySparkSnowflakePythonLLM APIsRESTWebhooksSlackGoogle WorkspaceNotion
Zeldan Labs agent architectureComposable by workflow
Inputs
Your systems
Documents
Email / chat
Databases / APIs
Data platforms
→
Agent layer
Zeldan Labs workflow
Extraction + validation
LLM reasoning
Business rules
Tool calls
Observability
→
Outputs
Decisions with context
Structured records
Alerts
Ranked options
Review queues
Access controlHuman reviewAudit trailFallback rules
Enterprise agent engineering
Put one to work.
Bring us one repetitive workflow. We map the inputs, systems, rules, exceptions and approval points, then decide whether it should become an agent, deterministic automation, or stay human.
Start with one repetitive workflow.3-step intake
01
Show us the work
The current documents, handoffs, systems and exceptions your team deals with.
02
Define the boundary
We identify what can be automated, what needs explanation, and where human approval stays.
03
Prototype on the real workflow
Test the interaction and outputs against realistic inputs before thinking about production rollout.
Have one repetitive process in mind already?
Start a conversation →