Software
Custom web applications, internal business systems, SaaS platforms, APIs, and integrations — built to be maintained, not just demonstrated.
Technology solutions & products
Bedrock Strategic designs and builds software, data systems, AI, automation, and digital products — for the companies we work with, and as products of our own. Bring a business problem. We work out what should be built, then build it.
One stack — we work at whichever layer the problem lives in
What we do
Problems rarely arrive labelled as an “AI project” or a “data project.” They arrive as something that costs too much, takes too long, or can’t be measured. We start there, and choose the technology afterwards.
Custom web applications, internal business systems, SaaS platforms, APIs, and integrations — built to be maintained, not just demonstrated.
Pipelines, warehouses, catalog and product data, market and financial datasets. Getting data correct, connected, and usable by the systems that need it.
Classification, document extraction, search and matching, decision support, and agents — applied where they measurably beat the alternative, and skipped where they don’t.
Software we own and operate ourselves — starting with a product information platform for small and mid-sized businesses, with more in the pipeline behind it.
The recurring manual work — reconciliations, imports, reports, hand-offs between systems — turned into something that runs on its own and tells you when it doesn’t.
Where technology actually pays back, what to build first, and the market, competitor, and operational intelligence needed to decide with evidence.
Capability pillars
A deliberately simple structure for a deliberately broad company. Most engagements draw on two or three of these at once.
Bedrock products
Consulting work funds product work, and product work sharpens consulting work. Everything below is Bedrock-owned software — built, operated, and supported by us.
A modern product information management platform for small and mid-sized businesses — the companies that need enterprise product-data capability without enterprise cost, consultants, or an eighteen-month implementation.
Enterprise product-data capability, without the enterprise complexity.
Bedrock PIM is in active development and is not yet generally available. No pricing or launch date is being advertised until it is.
| SKU | Product | Completeness | Status |
|---|---|---|---|
| BR-4471-AC | Air compressor, 2-cyl | Published | |
| BR-2210-SD | Brake shoe kit | Published | |
| BR-9083-FL | Fuel filter element | 3 missing | |
| BR-1140-EL | Alternator, 160A | AI draft ready | |
| BR-7752-CO | Coolant hose, upper | Published | |
| BR-3308-SU | Leaf spring assembly | Draft | |
| BR-6621-DR | U-joint, greaseable | In review |
CONCEPT INTERFACE · BEDROCK PIM
Working tooling from our parts-data practice — VMRS classification, interchange construction, and catalog normalization — being packaged into something distributors and software vendors can use directly.
Point-in-time pricing and availability histories built from public sources, structured for research teams. Data and methodology only — never signals or advice.
The utilities we build to deliver client work — extractors, matchers, monitors, reporting engines — are written to be reusable. The useful ones become products.
Industry expertise
Technology is transferable; context is not. These are the areas where we already understand the vocabulary, the data, and the way the business actually runs — which is usually the difference between software that works and software that gets abandoned.
Commercial vehicle parts, VMRS coding, interchange and cross-reference data, distributor and dealer catalogs, fleet maintenance data. Years of work inside this data, not a case study read about it.
Catalog quality, supplier feeds, channel publishing, search and findability, pricing operations, and the reporting that tells you which SKUs actually earn their shelf space.
Market and alternative datasets, research tooling, monitoring systems, and custom analytics applications. Data and engineering only — we don’t give investment advice.
Companies large enough to have a real technology problem but without an internal engineering team. Often the highest-return work there is, because the baseline is spreadsheets and re-typing.
Vendors who need a specialist for one part of the build: a data layer, an AI feature, an integration, a migration, or a prototype that has to become a real product.
Industries change, and so does what can be built. When a problem is a good fit for what we do, the sector it sits in matters less than whether technology can move the number.
Technology in action
Four representative build types, drawn from our own prototypes and product development. Client systems aren’t shown publicly — but this is the shape of what gets delivered.
| Branch | Orders | Fill rate | Trend | Status |
|---|---|---|---|---|
| Northeast | 4,812 | 96.2% | On target | |
| Midwest | 5,140 | 94.8% | On target | |
| Southeast | 3,996 | 91.3% | Watch | |
| West | 4,256 | 93.7% | Improving |
Numbers pulled from the systems that already hold them, reconciled once, and presented so an operator can act on the same screen where the problem appears.
Feeds arrive in whatever shape the supplier sends. The pipeline makes them consistent, records what it rejected and why, and fails loudly instead of quietly publishing bad data.
| Part | Description | Proposed code | Confidence | Action |
|---|---|---|---|---|
| A-4471 | Compressor, air, 2 cylinder | 013-001-001 | Auto-accept | |
| B-2210 | Shoe kit, brake, rear | 013-002-004 | Auto-accept | |
| F-9083 | Element, filter, fuel/water sep | 043-003-002 | Review | |
| E-1140 | Alternator 160A brushless | 031-001-003 | Auto-accept | |
| X-5518 | Kit, misc hardware, unlabeled | — ambiguous — | Human | |
| S-3308 | Spring assembly, leaf, front | 016-002-001 | Review |
Accuracy is measured against a held-out set and reported per batch — not asserted.
A model proposes, a confidence score decides whether it can be trusted, and anything below the line goes to a person. That structure is what makes AI usable on data that has to be right.
| Series | Coverage | Points | Freshness | Status |
|---|---|---|---|---|
| Component price index | Nationwide | 1,284 | T-1 | Current |
| Availability & lead time | Nationwide | 986 | T-1 | Current |
| Listing breadth | Top distributors | 742 | T-2 | Building |
| Category concentration | Selected | 310 | T-2 | Backfill |
Datasets and methodology only. No signals, recommendations, or advice.
Structured, point-in-time datasets and the tooling to interrogate them — for research teams, operators, and anyone who needs to know what was true on a given date rather than what the source says today.
Build
Most of what companies need isn’t exotic. It’s a system that holds the right information, shows the right people the right view of it, and does the repetitive part automatically. We build that — as a web application, an internal tool, an integration between systems that don’t talk, or a product with customers on it.
We work from prototype to production: something usable early, hardened once it’s clearly right, and documented so it can be handed to your team or kept running by ours.
Nothing exotic by default. Boring, well-understood technology is usually the right answer for systems that have to run for years.
| Name | Air compressor, 2-cylinder |
| Part no. | A-4471 |
| Aliases | A4471 · A-4471-AC · 4471A |
| UOM | Each |
| VMRS | 013-001-001 |
| Confidence | 0.97 |
Data
Product and catalog data is one of the areas where we go deepest. Four suppliers describe the same item four different ways, part numbers carry punctuation nobody agrees on, and attributes live in PDFs. That’s not a search problem — it’s a data problem, and it quietly limits everything built on top of it.
We deduplicate, normalize, extract attributes, build cross-references, classify, and deliver in whatever format your systems ingest. Then we tell you how accurate it is, measured on a held-out sample, rather than asserting that it’s clean.
Bulk assignment of Vehicle Maintenance Reporting Standards codes to parts catalogs and service records, so maintenance data becomes comparable across locations, vendors, and systems. Accuracy is measured and reported per batch.
Linking OEM, aftermarket, private-label, and competitor numbers that refer to the same physical part — including the one-to-many cases and the published interchanges that contradict each other. We flag conflicts instead of hiding them.
Supplier data consolidation, catalog enrichment for distributors and software vendors, and the reporting that turns service history into cost-per-mile, warranty recovery, and failure-rate analysis.
Intelligence
AI is one capability here, not the personality of the company. Some problems are a model; many are a well-written rule, a schema fix, or a report that didn’t exist. Choosing wrong is expensive in both directions — and most of the disappointment we see comes from a model being asked to do a job that a database constraint would have done perfectly.
Where a model genuinely wins — judgment at a scale humans can’t reach, messy language, documents, matching across variation — we build it properly: thresholds, human review, evaluation against a held-out set, and honest reporting of what it gets wrong.
The last row is the one that saves the most money. Some projects need a definition before they need a developer.
Financial technology & data
Building and maintaining datasets, research applications, monitoring systems, and analytics for people whose work depends on evidence. Our own background includes industrial pricing and availability data, which behaves as a leading indicator for freight and fleet activity.
Bedrock Strategic provides data, engineering, and methodology only. We do not provide investment advice, recommendations, trading signals, or portfolio management, and we are not a registered investment adviser.
Growth technology
Technology-enabled growth rather than agency retainers: structured prospect universes, enrichment, competitor and pricing monitoring, content and social analysis, and the automation that keeps it current without a person copying rows into a spreadsheet.
We build the machinery and hand over the operating manual. If you want an agency to run campaigns, we’ll tell you so.
How we work
The fastest way to find out whether something is worth building is to build a small, real version of it against real data — before anyone signs up for a long project.
A conversation about what’s slow, expensive, or unmeasurable — not about technology. We’ll say plainly if the answer is a process change rather than software.
A representative piece of the real work, priced up front, with a defined output you can judge. If it doesn’t hold up, you’ve spent a little and learned a lot.
Working software in visible stages, with the boring parts done properly: validation, monitoring, access control, documentation, and a way to roll back.
We can keep it running and improving, or document and transfer it to your team. Both are fine outcomes. Being difficult to leave is not a strategy.
About Bedrock
Bedrock Strategic exists to find the places where technology creates measurable value, and then build the thing. Sometimes that’s a system for a client. Sometimes it becomes a product we own and operate. Sometimes it’s a dataset, an automation, or a model — and sometimes the honest answer is that it shouldn’t be built at all.
The company is deliberately broad because the useful work is. What stays constant is the approach: understand the business problem first, choose the technology second, prove it on something real, and be straight about what it does and doesn’t do.
The name is the idea. Bedrock is what everything else gets built on — structured, load-bearing, and expected to still be there in ten years. That’s the standard we hold the work to, whether it’s a client system, a data product, or software with our own name on it.
Questions
Bedrock Strategic is a technology solutions and product company. We design, build, and operate software, data systems, AI applications, automation, and digital products — both for clients and as products we own. The work spans custom applications, data engineering, business intelligence, product information management, applied AI, financial and market data, and growth technology.
Anything where a clear business problem can be moved by software, data, or automation: a custom web or internal application, an integration between systems that don’t talk, a data pipeline or warehouse, a dashboard, a classification or extraction model, a catalog cleanup, a research tool, or a prototype that needs to become a real product. If a project isn’t a good fit for us, we say so early and try to point you somewhere better.
No. AI is one capability among several. We use it where it measurably beats the alternative — classification at scale, document extraction, matching across messy variation, language interfaces — and we use conventional software, data engineering, or a process change where those are the better answer. Choosing the wrong tool is expensive in both directions.
Both. Client work and product work fund and sharpen each other. Our first named product is Bedrock PIM, a product information management platform aimed at small and mid-sized businesses, currently in active development and looking for design partners. It is not yet generally available, and we don’t advertise pricing or a launch date until it is.
VMRS stands for Vehicle Maintenance Reporting Standards, a coding system maintained by the Technology & Maintenance Council for classifying parts, systems, and repair work on commercial vehicles. Assigning VMRS codes to a catalog or to service records makes maintenance data comparable across locations, vendors, and software systems.
Without it, the same repair is recorded five different ways and no one can measure cost per mile, warranty recovery, or failure rates reliably. We assign these codes at scale and report measured accuracy rather than asserting it.
A cross-reference, also called an interchange, links part numbers from different manufacturers that refer to the same physical part. It is what lets a distributor answer “what else fits this” when a customer arrives with an OEM number, and what lets a catalog offer substitutes when an item is out of stock.
Building one accurately is harder than it looks, because supplier numbering is inconsistent, one-to-many relationships are common, and published interchanges frequently contradict one another. We build them and flag the conflicts instead of hiding them.
Yes. We deliver in whatever format your systems ingest — CSV, Excel, JSON, a database load file, or an API endpoint — and we integrate with what you already run. We do not require you to move platforms, and for data work we usually don’t need production access; an export is normally enough.
We sign an NDA before receiving data, work only from the extracts required for the engagement, and do not resell, redistribute, or reuse client data in other products. If your data cannot leave your environment, tell us during scoping and we will discuss what is workable.
Mostly small and mid-size companies — distributors, dealer groups, fleets, software vendors, and operators — large enough to have a serious technology problem but without a dedicated engineering or data team. We also take on scoped projects for larger organizations where an internal team needs an outside specialist for one piece of the work.
No. Our financial work is data, engineering, and methodology: point-in-time datasets, research and monitoring tools, and custom analytics applications. Industrial parts pricing and availability are a useful alternative dataset because they move ahead of reported results — tightening price and availability generally indicate high freight and fleet utilization, and softening indicates slowing activity.
We build clean, documented versions of that history and license it to research teams. We do not provide investment advice, recommendations, trading signals, or portfolio management, and we are not a registered investment adviser.
With a scoping call, followed by a fixed-price pilot on a representative slice of the real work so you can judge quality before committing to more. Email hello@bedrockstrategic.org with a few sentences about the problem and what you need it to do.
A few sentences about the problem is enough to start — what it costs you today, what you wish the system did, or just the part that keeps breaking. If we’re not the right fit, we’ll say so and point you somewhere better.
Typical first reply within one business day. NDAs signed before any data changes hands.