Paid Discovery
Map every signal source. Architect every feed.
A focused engagement — scaled to your scope — that inventories every source of signal in your environment and produces a living data architecture your intelligent systems can depend on. Whether you're a solo operator, a growth-stage team, or a defense prime, Discovery starts where you are.
Your environment is full of signal. Your agents see almost none.
It doesn't matter if you're running a three-person shop or a thousand-person program. Every operation has signal sources that could feed intelligent systems: databases, spreadsheets, sensor networks, APIs, documents, customer conversations, market data, and the knowledge locked inside your people's heads.
Most of this signal is either invisible to agents, trapped in formats they can't consume, or scattered across systems that don't talk to each other. The model isn't the bottleneck. The feed is.
Discovery maps what exists, identifies what's missing, and architects the living data system that connects it all to your intelligent systems.
Humans are sensors too.
The most valuable signal in any organization is often unstructured and human: what operators know from experience, how field workers feel about a process, what sales teams hear in conversations, what engineers believe about technical risk.
Discovery includes designing structured sessions — recorded operator interviews, sentiment captures, tacit knowledge extraction — that turn human insight into qualified data your agents can consume.
An operator describing how weather affects their morning decisions is data. A technician explaining why they distrust a sensor reading is data. We architect the capture.
What We Map
Every source of signal in your environment.
Machine
Human
External
How It Works
Four phases. Scaled to your scope.
A focused operation could take a week. A complex enterprise environment could take a month. The phases are the same — the depth scales.
Inventory
We map every existing signal source — whether that's three spreadsheets and a CRM or hundreds of APIs and sensor networks. We identify what your intelligent systems can already see and what they can't.
Design
We design the feed architecture: what to collect, from where, how to enrich and score it, how to deliver it to your agents. For small teams this might be one MCP server. For larger environments, a full pipeline with connectors and attestation.
Validate
We test critical assumptions: can this data actually be accessed? Is the quality sufficient? Do the people who hold tacit knowledge have time and willingness to contribute? We run pilot captures where it matters.
Deliver
You receive a living data architecture matched to your scale: signal source inventory, feed specifications, enrichment design, delivery endpoints, human capture protocols where relevant, cost model, and implementation roadmap.
The Deliverable
A living data architecture blueprint.
Not a slide deck. A working architecture document that specifies every feed your intelligent systems need, how to build it, and what it costs.
Signal Source Inventory
Complete map of every data source in your environment — machine, human, and external — with access feasibility, quality assessment, and coverage gaps.
Feed Specifications
For each feed: source, enrichment pipeline, scoring dimensions, update frequency, delivery format (MCP, API, webhook), and data schema.
Human Capture Protocols
Structured session designs for extracting tacit knowledge, operator sentiment, and expert assessments into data your agents can consume.
Enrichment Pipeline Design
How raw signal becomes qualified intelligence: normalization, entity extraction, scoring, embedding, lineage tracking, and quality assurance.
Delivery Architecture
How feeds reach your intelligent systems: MCP server topology, API design, connector specifications, security model, and attestation layer.
Implementation Roadmap
Phased build plan with cost model, timeline, dependencies, and quick wins. What to build first, what to defer, and what compounds fastest.
Who runs a Discovery?
Anyone whose intelligent systems need better data. The scope scales to you.
Solo operators & small teams
You have a few data sources and agents that could be much smarter. Discovery gives you a clear build plan instead of guessing.
Startups deploying AI
Internal data locked in silos. Discovery maps how to make it agent-accessible before you waste months building the wrong pipeline.
Growth & proposal teams
Pipeline intelligence from scattered sources. Discovery architects the feed that makes every bid, pitch, or campaign sharper.
CNC shops & small manufacturers
Machine data, operator knowledge, and maintenance logs that could drive smarter operations. Discovery designs the capture.
Medical organizations
Clinical workflows, compliance data, and practitioner expertise that need structured capture for safe, effective AI.
Defense & government
BAA submissions, mission planning, and autonomous systems that need differentiated intelligence. Discovery maps the data advantage.
Industrial operations
Sensors, field reports, and operational telemetry that agents can't access yet. Discovery bridges the gap.
Portfolio companies & investors
Cross-portfolio data visibility. Discovery architects feeds that make every asset smarter.
Anyone whose agents need better data
You know the model works. You know the data isn't good enough. Discovery tells you exactly what to build.
After Discovery
Then we build it.
The architecture blueprint becomes the scope for a living data system build. You can build it yourself, bring in another team, or engage Adjective to build and operate it. The blueprint is yours either way.
Most teams choose to have us embed and build it together.
Stop guessing what your agents need. Map it.
Every signal source inventoried. Every feed architected. One blueprint your team can execute on — scaled to your scope, your budget, your timeline.