EXECUTION INFRASTRUCTURE FOR AI-NATIVE ORGANIZATIONS
AI is transforming work. TAB makes sure work actually gets executed.
TAB detects execution gaps, restores stalled work, and routes recovery to the person, system, or agent best positioned to act — without replacing existing workflows.
Built for enterprise pilots. Designed around real operational environments.
01 — WHERE TAB STANDS
The infrastructure is built. The proof is not. That is the point.
An honest read for both sides of the table — what exists today, what remains unproven, and why engagement now is what converts one into the other.
WHAT IS READY
The technical infrastructure exists.
- Core engine: friction-event detection across connected systems
- Recovery routing through existing channels (Slack, Jira, email)
- Adaptive wrapper expressing the fixed core per environment
- Anonymous-by-architecture data model
WHAT IS NOT YET PROVEN
The risk that funding removes.
- Pilot proof: 3–5 live environments validating recovery into value
- Native connector depth (Salesforce, HubSpot, Linear, dbt)
- The friction-event metric as a repeatable industry benchmark
WHY NOW
The window is the validation, not the build.
FOR DESIGN PARTNERS
Shape the recovery model inside your environment before it hardens. Your seams define the category.
FOR INVESTORS
Fund the validation, not more R&D. The infrastructure exists; the risk left is concentrated and removable.
PILOT-FIT STUDIO
Turn one stalled workflow into a testable pilot.
Describe the operating environment. TAB maps the breakdown, the minimum intervention, and a four-week measurement plan.
01 — THE THESIS
The AI layer is growing. The execution layer is missing.
SaaS optimized work inside tools. TAB recovers the work that falls between them.
Every team has a tool. No one has the workflow.
SaaS gave each team a purpose-built app, but work crosses teams, systems, and agents. No tool owns the handoff — so the handoff is where work dies.
Dashboards observe. They don’t recover.
Monitoring tools surface metrics and alerts, but watching a stalled workflow doesn’t restart it. Visibility without recovery is just a faster way to watch work fail.
Automation fixes the repeatable. The rest still stalls.
RPA and workflow tools handle the path you already mapped. The work that stalls is the unplanned, the ambiguous, the cross-system — the work no automation was built for.
Failures live between intent and action — across people, permissions, tools and teams. The missing layer is not another app. It is the infrastructure that coordinates and recovers across them.
02 — PRODUCT ARCHITECTURE
One execution layer across the organization.
TAB sits as a horizontal coordination and recovery layer — connecting leadership, managers, employees, enterprise systems and AI agents without replacing any of them.
It observes in context, detects the exact breakdown, and triggers recovery inside the environments work already happens in.
Diagram: TAB forms a horizontal layer spanning leadership, managers, employees, enterprise systems and AI agents, acting as the coordination and recovery interface between them.
03 — CAPABILITIES
The execution loop: observe, detect, recover, learn.
Detect
TAB measures friction events in the workflow, in-flow — not people. Aggregate and anonymous by architecture. It counts events, not people; it bypasses, not alerts.
Coordinate
TAB routes the right action to the right actor — human, manager, or AI — inside existing tools, permissions and environments.
Recover
Stalled work is picked up and returned with continuity preserved — context, status and next step intact across systems and handoffs.
Learn
Each recovery trains the layer. Recurring breakdowns surface as structural patterns, not individual signals.
04 — THE DIFFERENTIATOR
The infrastructure stays constant. The operating layer adapts.
SELECT A USE CASE
ADAPTIVE WRAPPER
Customer Operations
Recovery embedded in case workflows; handoffs restored before SLA breach; AI suggestions routed inside approved tools.
FIXED CORE ENGINE
Core Engine
- Observation logic
- Breakdown detection
- Recovery orchestration
- Continuity model
Same core engine. Different operational expression.
05 — USE CASES
One core engine. Three places execution breaks.
The infrastructure stays constant. Hover a use case to see how its adaptive wrapper recovers stalled work — without replacing the tools your teams already use.
FIXED CORE
Core Engine
- Observation logic
- Breakdown detection
- Recovery orchestration
- Continuity model
NOW EXPRESSING
IT Governance
Same core engine. Different recovery expression.
05 — HOW IT WORKS
A closed loop, not a dashboard.
Observe context
TAB reads the operational context where work already happens — tools, roles, handoffs and status.
Detect the exact breakdown
It identifies the specific point where execution has stalled — not a score, an event.
Trigger the lowest-friction recovery
It routes the smallest action that unblocks work to the right actor, in-flow.
Return work with continuity
Work resumes with context, status and next step preserved across systems.
OUTCOME METRICS
Pilot metrics are currently being defined with design partners.
SEE THE MECHANICS
Where the seams get recovered.
TAB sits across the handoffs between your existing systems. When a cross-tool handoff stalls, the layer intercepts it, routes the smallest action that unblocks it, and returns work with continuity — anonymous by design.
Diagram: source systems (CRM, ITSM, Tickets, Pipelines) hand off work down through the TAB coordination and recovery layer, which detects friction events, routes the smallest unblocking action, and returns continuity to destination systems (Sales, DevOps, Support, Analytics). The layer observes in context, is anonymous by architecture, and requires no new system to adopt.
A cross-tool handoff stalls — the seam between two systems goes silent. TAB sees it where work already happens.
The layer triggers the minimal step that unblocks the handoff — not a new task, not a new dashboard to watch.
Work resumes inside the destination tool with full context intact. No context switch, no rework.
06 — WHY NOW
Every company is becoming AI-native. Most are not execution-ready.
SaaS gave every team its own app. It never gave the organization a way to execute across them. The next bottleneck is not intelligence — it is the infrastructure to act on it.
Stanford/MIT randomized trial of 5,179 contact-center agents — AI assistance raised productivity +14% on average and +34% for novice and struggling workers, with improved retention (Brynjolfsson et al.).
Gallup 2026 — global engagement at 20%, an estimated ~$10T in lost productivity.
DEX market growing from $1.32B (2023) toward $2.97B (2031), with Gartner projecting enterprise adoption rising from 15% to 50% by 2027.
SaaS tools were built to optimize work inside each team. None were built to recover the work that falls between them. As AI multiplies what each tool can do, the seams widen — and the cost of dropped handoffs compounds. The fix is not another app. It is infrastructure: a layer that detects the gaps and routes recovery across the entire stack.
07 — WHY NOT EXISTING TOOLS
Existing tools weren’t built for the seams.
Automation moves data. Assistants generate inside a conversation. Monitoring watches people. None of them recover stalled work.
Automation platforms
Workato · Zapier · n8n
Move work between systems on a trigger. They don’t detect when execution has stalled, and they can’t recover a handoff that fell through the seams.
AI assistants
Copilot · ChatGPT · Claude
Generate inside a single conversation. They don’t hold the organizational context around the task — the permissions, the roles, the handoffs where work disappears.
Employee monitoring
Productivity surveillance
Watch people to measure effort. TAB measures friction events, not people — aggregate and anonymous, built to bypass breakdowns rather than surveil behavior.
08 — ROADMAP
From pilot to category.
NOW
Pilot
Embedded pilots with 3–5 enterprise design partners across customer operations and AI transformation. Validate breakdown detection and recovery in live environments.
NEXT 6 MONTHS
Embed
Deepen integrations across the environments work already happens in. Move from detection toward autonomous recovery inside approved guardrails.
12 MONTHS
Scale
Repeatable deployment across functions. Turn pilot evidence into a category — execution infrastructure for AI-native organizations.
09 — EARLY VALIDATION
Validation where execution breaks first.
US design partnership
A live design partnership embedded in a trading workflow, validating execution recovery in a high-stakes, high-friction environment.
Call-center field research
Field research focused on extreme early attrition and the operational friction that drives it — the seam where execution breaks first.
Behavior-first AI prototypes
Prototypes testing intervention timing, trust and low-friction recovery — proving the loop can act without surveillance.
Early-stage validation. Pilot metrics are currently being defined with design partners.
10 — OPERATIONAL METRICS
The numbers behind execution recovery.
A measurable loop, not a dashboard of opinions. These are the operational metrics TAB is built to move — and the validation footprint behind them.
From friction-event detection to a routed recovery action — the core execution metric TAB is engineered around. The loop that turns intelligence into done.
Active discussions across customer operations and AI transformation.
A taxonomy derived from field research where execution breaks first.
Cross-system handoffs documented across pilot environments.
No employee monitoring, sentiment detection, or behavioral scoring — by design.
Design targets and current validation footprint. Pilot KPIs are being formalized with design partners. All measurements are aggregate and anonymous.
11 — FOUNDER
Built by a systems architect focused on the gap between knowing and doing.
Danya Dotan combines behavioral science, systems thinking and AI product design. Her work focuses on execution recovery, operational continuity, human–AI collaboration and the infrastructure organizations need to adopt AI through trust rather than surveillance.
Danya Dotan · Founder, TAB@Work
11 — BUILD WITH US
Build the execution layer with us.
We’re looking for the operators and investors who see the same bottleneck.