Vision: your AI utility bar for growth teams.
We are building a living strategy layer that routes the right AI agents, data sources, and workflows to produce measurable marketing and sales outcomes. UtilityBar.ai keeps teams focused on analysis and relationships while automation and intelligence handle the repetitive lift.
- Create a shared system that understands your offers, ICP nuances, and proof points.
- Automate the generation of briefs, plays, and campaign assets with contextual guardrails.
- Measure impact through the work products shipped, not just prompts used.
Technical architecture requirements
Model-agnostic orchestration
UtilityBar.ai treats models as interchangeable components. We optimize for speed, transparency, and controllability rather than betting on a single vendor.
- Abstract away proprietary dependencies and keep optionality across frontier, open, and proprietary models.
- Compose agents that can be swapped or retrained as new capabilities emerge.
- Instrument every step for cost, latency, and accuracy trade-offs.
Context fabric & governance
- Integrate CRM, marketing automation, product usage, support, and open web data with rigorous change tracking.
- Maintain a source-of-truth memory of campaigns, offers, credibility markers, and past performance.
- Expose dual interfaces so non-technical SMEs can compose flows while technical teams extend retrieval and RAG systems.
Context graph
- Capture relationships between personas, accounts, offers, and proof points.
- Blend structured data with unstructured assets for richer prompting.
- Track revisions so the system knows what “good” looks like inside your org.
Automation layer
- Chain specialized agents for research, synthesis, creative, and QA.
- Route approvals and enrichment to the right humans when needed.
- Publish outputs directly into the tools teams already use.
Feedback & telemetry
Close the loop on what ships, what converts, and where friction remains.
- Observe edits, approvals, and downstream engagement.
- Feed learnings back into prompts, retrieval, and agent routing.
User base strategy
- Marketing and sales subject matter experts who need leverage and packaged insights.
- Technical AI developers and engineers extending retrieval, agents, and integrations.
- Data engineering teams responsible for infrastructure, governance, and telemetry.
- Cross-functional squads pairing domain expertise with technical implementation.
Current development focus
Flexible context management
- Designing systems that surface the right mix of company, product, and market data for every workflow.
- Balancing deterministic retrieval with adaptive, agent-driven exploration.
Ease-of-use meets extensibility
- Creating configurable templates, blueprints, and “recipes” that SMEs can run without code.
- Ensuring technical teams can plug in custom retrieval, evaluations, and deployment targets.
Shared telemetry
- Instrumenting human feedback and outcome data to inform prioritization.
- Building dashboards that explain what shipped, what converted, and why.
Strategic pilots
- Running targeted engagements to pressure-test the platform in real marketing and sales motions.
- Translating learning into reusable frameworks and UtilityBar components.
Engagement roadmap
Strategic alignment
- Clarify growth objectives, workflows, and the work products that move needles.
- Map required data sources, access patterns, and governance constraints.
- Document success metrics that tie directly to revenue outcomes.
Build, test, learn
- Rapidly prototype agent chains and automations against live datasets.
- Instrument for signal quality, latency, handoff friction, and adoption.
- Convert pilots into repeatable playbooks with shared telemetry.
Context fabric
Agent playbooks
Enablement
Security & trust
Isolation
Provision dedicated tenancy/VPC options with clear boundaries between customer datasets and agent execution.
Access
Operate on least-privilege principles, support SSO, and audit every retrieval and action issued by humans or agents.
Models & compliance
Control model selection, data residency, and training opt-outs; document DPAs and lineage for every deployed flow.
FAQ
How is UtilityBar.ai different from a chat interface?
We orchestrate persistent agents, retrieval, and automations that output finished assets—campaign briefs, nurture sequences, account plans—without asking teams to prompt from scratch each time.
What data do we need to start?
Begin with core company materials, CRM exports, and sample deliverables. We progressively layer product usage, support, intent, and public data as the context fabric matures.
How do non-technical SMEs contribute?
They assemble recipes from pre-built blocks, review generated work, and provide feedback that trains the system. Technical teams can extend the same recipes with custom logic when needed.
How do you measure success?
We track the work products shipped, the revenue motions they support, and downstream metrics—meetings, pipeline, influenced revenue—against the goals set at kickoff.
Can this respect our security posture?
Yes. We deploy in dedicated environments, honor your access controls, and document lineage plus audit trails for every agent action.
Resources & background
Strategy working doc
Living articulation of the UtilityBar.ai vision, architecture decisions, and open questions. Updated as pilots inform the roadmap.
Meeting transcript
Reference discussion outlining the UtilityBar approach to marketing and sales automation, including data architecture and adoption topics.
Related initiatives
Launch Guardian, Pitch Mesh, and Inbound Found provide adjacent capabilities we draw from when building UtilityBar playbooks and automations.
UtilityBar.ai distills these learnings into a single, opinionated execution layer for marketing and sales automation.
Get started
Book a 30‑minute strategy workshop
Identify the highest-impact automations, data prerequisites, and success metrics to pilot UtilityBar.ai inside your org.
- Assess current marketing & sales workflows and friction points.
- Inventory available data, context, and proof assets.
- Outline a pilot that proves measurable impact quickly.