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Tango's path from workplace analytics to an agentic operating system, co-built with Thoughtworks.
Ungoverned agentic AI is not a future threat. It is current state. The window to do this strategically is open now.
Becoming agentic is not a technology project. It is a category of company. The destination that gives every modernization decision a purpose.
Enterprise ChatGPT accounts. Copilot licenses. No systems, no governance, no outcome model.
Scattered agents, no control plane. The messy middle. Most organizations are stuck here, trying to contain agents instead of harnessing them.
Agents writing, testing, releasing. Anthropic-class operating model. End-to-end observability, governance, and economics by design.
Lineage, quality, and access controls across Core, WatchWire, AgileQuest, and Locatee — so agents can synthesize the data that is Tango's moat.
Token cost is a P&L line item. FinOps, model routing, and cost per outcome — so every agent's margin is known before it scales.
Control plane before agent sprawl. Policy, audit, and human oversight by design — and ASC 842 / IFRS 16 / SOC 2 by default.
These are not values on a wall. They shape every commercial, architectural, and team decision in the work that follows.
The scope of this engagement is three segments, 48 weeks, fixed-fee-for-outcomes. Phase 2 is not in scope — it is an optional extension whose shape is decided jointly at the M3 gate.
Fixed-fee for outcomes. Gated segment commitments. Each milestone gate is both an acceptance checkpoint and a scope elaboration point — so commercial specificity scales with what we actually learn.
Three segments. Each segment requires the prior gate's outcomes to be approved before investment commits.
Not time and materials. Each segment is priced against defined outcomes and measurable success criteria.
Segment 1 outcomes are fully defined at start. Segment 2 and 3 outcomes are baselined as a deliverable of the preceding segment.
An ELT-ready implementation plan within 30 days of engagement start. Architecture, plan, first-agent prototype results.
Throughout Segment 1, we'll use AI/works to rapidly prototype agent concepts and evaluate them with design partners — focused on testing the desirability and value of the proposed agentic capabilities, and capturing feedback that shapes the initial agent portfolio's design and prioritization. This demo is one example of that craft, built in days. The real first agent is selected, prototyped, and validated with you inside Segment 1.
Every segment is measured against the outcomes Tango's own ELT proposal laid out: reposition the market narrative, unlock the acquisition moat, and get ahead of the AI-native upstarts before they expand beyond their initial niches.
From "legacy IWMS" to "AI-first workplace platform." Re-open deals Tango is currently losing to AI-native entrants like VergeSense, Density, and Facilio — and the category-shift buyers like Apple and NVIDIA.
The shared foundation layer lets existing customers benefit from AI capabilities without a forced platform migration. Continuity for today's customers while the new platform matures.
WatchWire, AgileQuest, and Locatee finally compound instead of fragmenting. Lease + occupancy + energy data — in one agent — is what no point-solution can match.
Shared foundation delivers value even if agentic adoption takes longer than planned. The data work is load-bearing either way — agents are the upside, not the whole bet.
Shared foundation under active development. First agent working prototype. 3–5 design-partner customers committed. Market signal that Tango is no longer a legacy player.
First agents in closed beta on real customer data. Project Hope and Project Empire substantially complete. Market narrative shifted. Pipeline and employee base re-energized.
New AI platform generally available with initial agents. Customers migrating through the shared foundation. New acquisition driven by AI value proposition. Competitive losses declining.
Each segment leaves Tango with a concrete asset, not a deliverables binder. Thoughtworks retains rights to its own platforms; everything produced for Tango belongs to Tango.
Because this is a fixed-fee-for-outcomes engagement, the composition flexes to the work. Six capability archetypes scale across 48 weeks alongside Tango's founding AI platform team.
Engagement vision, ELT alignment, implementation plan ownership, milestone readouts. Owns design-partner strategy and GTM enablement. Includes delivery transformation leadership for the AI-First operating model and waterfall-to-agile transition.
Shared foundation architecture, AI platform target-state design, agent architecture, agentic workflows, LLM integration, control plane configuration. Builds alongside Tango engineers with progressive ownership transfer.
Cross-product data model, integration patterns, data readiness, governance, scalable foundations for agent context and reporting. Schema reconciliation across Core, WatchWire, AgileQuest, Locatee. Tapers as the foundation stabilizes.
Agent evaluation rigor: synthetic data validation, agent outcome measurement, evaluation harness ownership, design-partner beta measurement. Secondary coverage of traditional QA alongside Tango's QA function.
Technical oversight of AI/works (reverse engineering, prototyping, forward engineering acceleration) and Agent/works (control plane reference architecture, observability, governance). Embedded across teams and workstreams.
Product Owner, CRE Domain SME, Product Designer / UX Lead, QA Engineer, and 5–6 Platform Engineers. Co-development from day one ensures the platform is Tango's to operate, not just Tango's to receive.
Both platforms accelerate this engagement. AI/works powers our delivery from day one. Agent/works is the licensed control plane for Tango's ADP and agent portfolio — with favorable terms if Tango participates as a design partner.
Four governance tiers, calibrated by altitude. The top risks are named and mitigated in the contract, not buried in an appendix.
Extraction is Tango-led (Project Empire). TW designs the shared foundation to consume extracted services, not raw ADF artifacts. Dependency tracked explicitly from Segment 1 via weekly Track 1 coordination.
Segment 1 data estate assessment provides early visibility. Foundation designed to accommodate heterogeneous schemas. Segment 2 scope bounded to highest-readiness data domains; later domains re-sequenced as clarity develops.
Portfolio sequencing validated at M1 against actual data and design-partner feedback. Tango co-development capacity sized for sustained delivery. Agents 3–5 may re-sequence to Phase 2 if capacity falls short.
Selection criteria defined in Segment 1 with Tango sales leadership. Minimum viable design-partner profile established early. Fallback: agents proven on synthetic data with real-data validation deferred.
Platform team fenced off from legacy operations per the reinvention proposal. TW co-sourced model provides capacity buffer. Weekly steering surfaces capacity risks; scope bounded at milestone gates.
Delivery transformation lead dedicated across all three segments. Change management plan developed in parallel with technical delivery. GTM framed around outcomes, not automation.
Six items sit on the critical path. Each is named, owned, and surfaced at the right governance tier — so a dependency slip becomes a steering conversation, not a Segment 3 surprise.
Stored-procedure extraction directly gates shared foundation integration timeline. Weekly Track 1 cadence established in Segment 1 to maintain critical-path visibility.
Customer availability and legal/data-sharing agreements must be in place before the closed beta in Segment 2.
Data warehouse maturity (Redshift consolidation) and API availability assessed in Segment 1. Material gaps may require scope adjustment at M1.
Delivering the full agent portfolio in Segment 3 requires sustained Tango co-development capacity (5–6 engineers) across multiple concurrent workstreams. Shortfall may re-sequence agents 3–5 into Phase 2.
Agents 3–5 require data domains beyond lease data — occupancy, energy, maintenance, facilities — extended by mid-Segment 3. Coverage gaps may require agent re-sequencing.
Milestone gate decisions must land within one week of readout to maintain engagement momentum and team continuity. Built into the executive cadence.