The real estate command center for contacts, deals, data, and next actions.
Clean up seller lists, check them against public records, and see exactly what is missing. Then decide the next follow-up with the evidence in front of you — nothing leaves the system without your approval.
Start where the work isOne reviewable workflow
From source row to trusted next step
Evidence stays attached while the operator decides what happens next.Imported source
Property18 Oak Street
OwnerNeeds review
Follow-upNot selected
Step 1
Bring in the list
Keep each source attachedStep 2
Check the records
Surface gaps and conflictsStep 3
Review what changed
Nothing updates silentlyStep 4
Approve the next step
Act with a record of whySource proof stays visible
Review before CRM changes
Approved next steps
Role paths for real estate operators
Source proof included
Record outcomes manually
How OrbiLattice works
One connected path from opportunity to conversion
Start with the work you already have, add the products that fit the job, and keep the operator in control as evidence and next steps move across the workspace.Across every stage
Priorities and assistant support stay connected to the work.
Stage 1
Find opportunities
Turn authorized lists and supported public records into reviewed opportunity work.Stage 2
Evaluate a property
Bring source-attributed property context, underwriting, and operations into review.Stage 3
Progress the deal
Keep deal context, owners, documents, and next steps visible as work progresses.Stage 4
Communicate and convert
Prepare relationship and outreach work with explicit approval and provider boundaries.Free workspace foundation
Explorer CRM
Bring contacts and authorized lead lists into an organized, reviewable workspace.The Single Platform for Real Estate Intelligence
Move from source intake to seller action, property math, pipeline handoff, and buyer context while keeping approval gates visible.
Open Operating MapBring messy market inputs into one review flow
Start with public records, spreadsheets, source lists, or CRM history, then move records into a sourced review queue instead of another disconnected import.Source intake
List cleanup
Seller signal review
💎 What is in the platform
Five core modules, and the honest edge of each one
You can turn on only the modules the work needs. Each one below links to a page that spells out what it does today, where it stops, and what it costs.
Early
Relationship review, which suggests who in your own contacts is closest to a person you are trying to reach, is real but early. It reads only contacts your workspace already owns, its strength score describes how good the evidence is rather than how confident we are about a person, and a human decides every introduction. We would rather label it than oversell it.Live Interactive Graph
Synthetic Persona Data
Interactive Network Topology
Click nodes to view relationship types, deal-sourcing scores, and entity intelligence.SJ
Sarah Jenkins
Principal Investor • Horizon Capital GroupAustin, TX
28 Connections
88% Diversity
89/100 Health
Deal Sourcing Priority
🎯 Strategic Warm Paths
Maps multi-hop introduction routes (e.g., You → Sarah → Mike) so you never reach out cold.⭐ High-Probability Sourcing
Highlights repeat partners and investors with verified liquidity and off-market deal flow.⚡ Automatic Construction
Built directly from your emails, transactions, and CRM history without manual entry.Daily Review Queue
Mission Control shows who needs attention next.
Mission Control gives your team a daily review queue for follow-ups, deal risks, list cleanup, and buyer matching. When an item needs judgment, Decision Console shows the proof, deal math, and risk before anyone approves the change. After the action, operators can record what happened and see the suggested follow-up.
Confidence-Weighted Transparency
OrbiLattice shows more context when the next step is uncertain. Strong evidence can move faster; conflicted or incomplete information stays in review.High
Ready to review (Strong sources)
- Sources align
- Action can be approved
- Audit context included
Mixed
Review needed (Some gaps)
- Conflicts surfaced
- Operator sees alternatives
- Edit before changes
Low
Hold for judgment (Missing context)
- Missing data called out
- Multiple options presented
- Human decision required
Traditional CRMs (Data-First)
1. Show property details2. Agent figures out what to do3. Multiple clicks to prepare the next action4. Generic recommendations5. Result: the operator rebuilds context by hand
Mission Control (Action-First)
1. Show prioritized actions2. Proof embedded in review cards3. Approve, edit, schedule, or reject4. Keeps evidence and audit context attached5. Result: follow-ups, updates, and outcome checks ready for review
Connected context across your business
A document lands where the work is
Property contextThe parcel and owner record the document refers to
Deal healthContract risk raised on the deal card, with the clause cited
Lead reviewQualification evidence attached to the follow-up it justifies
Task queueHigh-risk clauses become approval tasks, not silent changes
What a review item can draw on
Lead priority, with the factors that produced it
Investment calculator results and their inputs
Tasks and deadlines raised from documents
Deal health computed from contracts and activity
Property and owner records with their source
Notes and document risk flags with the text they came from
One document, five places it matters
A contract is not just a file. It changes what you know about the property, the person, the deal, and what has to happen next.Contract or list
Uploaded by youProperty Intel
Parcel and owner contextLead review
Evidence for follow-upMission Control
Queued for a decisionTask queue
Deadlines and blockersDeal pipeline
Stage and risk on the cardWhat the review queue does with it
Document uploadRisk notes are drafted for a person to read, never applied on their own
Priority feedItems needing judgment surface first, with the source that raised them
Linked contextOne review item carries its contact, deal, and task together
Reviewed actionsApprove, edit, or reject, and the change history keeps what you chose
Follow-up remindersDeadlines and blockers become tasks with a date attached
Recorded outcomesLog what actually happened, and see the next step it suggests
Traditional CRM vs. Mission Control
The difference is not how much data you can store. It is whether the next step arrives with the reason for it attached.| Feature | Traditional CRM | Mission Control |
|---|---|---|
| Data Organization | Siloed by entity type | Connected Intelligence Fabric |
| Insight Discovery | Manual reports | Queued by priority for review |
| Decision Context | Rebuilt manually | Packaged with sources |
| Cross-Entity Linking | Manual lookups | Automatic with one-click navigation |
| Document Intelligence | Static file storage | Active risk notes + review tasks |
| Lead Scoring | Rules-based | AI + document qualification |
| Deal Health | Manual tracking | Auto-computed from documents + activity |
| Relationship Introductions | None / Manual outreach | Ranked warm paths + suggested messages |
| Network Health | Invisible until failure | Real-time strength + risk factors |
| At-Risk Relationships | Reactive after silence | Early decay detection with alerts |
| Path Discovery | Manual research & guesswork | Multi-hop optimal connection mapping |
Built so it cannot quietly make things up
The failure mode that matters in this category is software that invents a plausible number when a lookup fails. These are the mechanisms that stop it.A failed lookup shows as failed
When a source is unavailable the surface says so. It does not fall back to a sample figure, and there is an automated test suite whose only job is to fail the build if fabricated-looking data reappears.Evidence decides how much review you see
Strong, agreeing sources take a shorter path. Conflicting or missing data forces the fuller explanation before anything can be approved.A person approves the change
Proposals are prepared, not executed. Outreach, offers, matches, and document actions all wait behind an explicit approval, and the record keeps who approved what.Review Queues That Reduce Manual Guesswork
Mission Control does not promise a universal time-saved number. It concentrates the manual review work that slows investors and wholesalers down: documents, lead priority, deal health, and follow-up tasks.Docs
Document Review
Manual contract analysisRisk notes and missing terms queued for approvalLeads
Lead Prioritization
Manual scoring and researchSource-backed priority and motivation cuesDeals
Deal Health Checks
Manual status trackingHealth checks tied to documents and activityTasks
Task Management
Manual task creation and trackingFollow-up work prepared with context attachedOutcome: less context rebuilding before action
Review items keep sources, confidence, missing data, and approval controls together.
Human-Approved Workflow, Not Blind Automation
Manual CRM workflow:
1. Find the latest contract or lead list2. Read through records manually3. Research missing clauses or owner context4. Update contact and deal records5. Create follow-up tasks from memory
Mission Control workflow:
1. Import the list, contract, or deal notes2. Mission Control shows the review item with sources and gaps3. Review the explanation, missing data, and proposed action4. Approve, edit, schedule, or reject before updates move forward5. Record the manual outcome and review the suggested follow-up
Result: approval-ready follow-ups with context attached and the operator still accountable.
Public records
Coverage you can check before you trust it
Most tools quote one coverage number and leave you to find out where it breaks. OrbiLattice publishes the whole list in three tiers, names the five sources it can pull from automatically today, and shows the terms attached to each one.
3,221
county-equivalents resolve by name
Every US county, parish, borough, and independent city, from the Census Bureau 2020 FIPS list. Resolving a place is not the same as having data there, and the app says which you have got.85
sources listed, across all 50 states
Shown in tiers that make the strength of each claim explicit, rather than one undifferentiated "coverage" number.18
reviewed for rights and limits
Each one carries its jurisdiction, what the data describes, and the terms it may be used under.5
available for automated retrieval today
Montgomery County PA, Philadelphia OPA, Lynchburg VA, Cook County IL, and the New Jersey statewide assessment roll.Three tiers, because they are three different strengths of claim
These are the same labels the source list uses. Filtering to any one of them tells you exactly what has and has not been verified.
Reviewed sources
18
Found, not yet reviewed
2
Portals not yet investigated
65
Coverage is only useful if it turns into leads
Lead derivation reads the county records your workspace has approved, so what you can work is decided by the jurisdictions you add rather than by a data vendor’s footprint.
Leads come from the counties you bring in
Add the jurisdictions you actually work, then derive property leads from those records. Nothing is capped at a vendor’s footprint, and an empty market means it is not ingested yet — not that it holds nothing.No separate data subscription to get started
Derivation reads the public records your workspace has approved. A licensed vendor extract stays available if you have one, but it is no longer what the feature runs on.Every lead is a property, with its receipts
A derived lead carries its county, parcel, assessed value, how long the owner has held it, and the date the record was read. It identifies a property, not a person.The limits are part of the product, not the fine print
Retrieval is capped at 25 rows per pull, against a fixed reviewed column list, in a deterministic order.
Owner and mailing-address columns are blocked at the source declaration for sources whose terms exclude them.
Every staged fact keeps its source and the date it was read, so a reviewer can check where a number came from.
Exports are attributed and hash-verifiable, and are gated per source by that source’s redistribution rights.
Explainable AI
See the 'Why' Behind Every AI Decision
Every recommendation should show the sources, confidence, missing data, and reasoning trail before an operator approves outreach, matching, documents, or pipeline changes.
Confidence‑Weighted AI
Persistent AI Workspace
Source Attribution
Approval Gates
Missing Data Flags
Reasoning Trails
Traditional "Black Box" AI
"This lead is hot" (why?)"AI suggests sending this property" (based on what?)"High confidence match" (how was this calculated?)Result: operators rebuild the evidence before trusting the recommendation
OrbiLattice Explainable AI
"Score based on: source freshness, owner signals, deal math, and buyer fit""Property matches because: geography, budget, asset type, and stated criteria align""Confidence reflects aligned sources, recent activity, and missing-data status"Result: faster review with evidence visible before action
Built-In Transparency Layer
Factor Breakdown
Visual charts showing how each factor (location, price, timing) contributed to the scoreDecision Tree
Step-by-step reasoning path from input data to final recommendationConfidence Scores
Confidence, data sources, and reasoning history where the workflow has enough contextSource Attribution
Data points carry source, freshness, confidence, or user-entered context where availableExample: Property Recommendation Explanation
AI Recommendation: Review 123 Oak Street for a buyer match
Confidence: strong source alignment • Generated: demo exampleWhy This Property Matches:
• Location Preference: aligned — Near the saved Riverside District search area• Price Range: aligned — Listing price fits his saved pre-qual range• Property Features: aligned — 3 bed / 2.5 bath matches his "must-have" filter criteria• Timing: review soon — New listing and recent buyer activity
Historical Pattern Analysis:
The packet can show recent buyer activity, saved criteria, and prior engagement so the operator can decide whether the match is worth outreach.AI-Generated Action Plan:
1. Draft Property Alert — Include the sources and match reasons for review2. Attach CMA — Add supporting deal math when available3. Follow-Up Timing — Queue a suggested follow-up cadence for operator approval
Operator check: approve, edit, or reject the outreach before any message is sent.
Pricing paths
Four bundles, priced around the work
Each bundle turns on a specific set of core modules. Pick the one that matches the job you do most, or take the full platform when pipeline, campaigns, documents, and matching all need to live in the same loop.
Power-ups such as Client Portal, Match Automation, and AI Dialer are added on top of a bundle and are listed with their requirements on the pricing page.
Find Your Workflow
Choose the path that matches your real estate work
Pick a role and a job. The selector returns approved public routes only: command-center workflow, product pages, pricing paths, workflow packs, or guided pilot language.
Who are you closest to?
What should the system help with first?
Recommended path
Focus on seller list intake, deal math, buyer matching, and approved follow-up.Best first step
Opportunity Engine
Turn messy records, public sources, and CRM history into reviewable packets.Core module
Lead Engine
Review how sourced lead records, context, and next actions fit together.Try a bounded job
Review workflow packs
Use a capped one-time path when you want proof around one job first.Best first step
Opportunity Engine
Public routes only
No CRM data access
No generated claims
FAQ
Questions teams ask before switching
Everything from MLS data strategy to agent onboarding. Transparent answers so your legal and operations teams are aligned.
OrbiLattice connects AI to approved workspace data and app actions so it can prepare calculators, PDFs, and record updates for review. The important part for operators is that sensitive changes still wait for approval instead of happening in a black box.
Zapier connects apps via simple triggers. OrbiLattice Workflows are built around real estate evidence: repair signals, property math, owner context, and pipeline stage. AI can recommend routing rules and prepare updates, while sensitive changes stay behind approval gates or explicit user-configured rules.
Yes. We have one-click importers for Follow Up Boss, kvCORE, and HubSpot. Our AI will even analyze your old workflows and suggest optimizations during the import process.
We use a human-in-the-loop system. Clear, low-risk actions can be queued for faster review or run under explicit user-configured rules. Sensitive outreach, document, pricing, and matching work is flagged for your approval in Mission Control. You always have final say.
Available controls include audit logs, risk flags, approval history, and identity or retention options by plan and configuration. Compliance-sensitive work should still be reviewed by the operator and their legal or brokerage process.