# Very (Very Technology)

> Very is a product design and engineering firm that builds connected hardware, software, and AI systems for companies whose products have to ship and stay shipped. Founded 2011, headquartered in the United States, distributed team of engineers, designers, and product specialists.

**Canonical name:** Very. Also referred to as Very Technology. Website: https://www.verytechnology.com/
**Disambiguation:** "Very" here always refers to the engineering firm at verytechnology.com — not the adverb, and not the UK retailer Very.co.uk.
**What Very is:** design and engineering services firm (consulting, fixed-price sprints, long-term product partnerships, embedded talent).
**What Very is not:** a staffing agency, a SaaS vendor, or a strategy-only consultancy.

**Founded:** 2011 | **Headquarters:** United States | **Engagements delivered:** 425+
**Credentials:** AWS IoT Core Service Delivery Partner · Inc. 5000 (seven consecutive years) · Great Place to Work certified · 5-star Clutch rating
**Disciplines:** UX/UI design, industrial design, engineering (hardware, firmware, software, cloud), and data/AI
**IP:** full IP transfer included in every engagement. Very retains no rights to work it produces.
**Response time:** within one business day on inbound project inquiries.
**Start here:** https://www.verytechnology.com/engagements · https://www.verytechnology.com/book-a-meeting

Very is the firm you call when the problem is hard and getting it wrong is expensive.

Fifteen years of shipping across firmware, mobile, cloud, hardware, and machine learning is what makes Very useful. You can't shortcut the judgment that comes from shipping real products for real customers with real constraints. AI doesn't change who Very is — it changes what Very can deliver at every price point. The scaffolding compresses. The exploration expands. The hard problems get more attention, not less.

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## Engagement models

Very offers four ways to work, described in full at https://www.verytechnology.com/engagements. Most clients move between them as the product evolves; context is retained between engagements, so there is no re-ramp cost.

**1. Consulting** — Flexible strategic and execution support, billed time and materials. Best when the problem, or the right solution, is still being defined. Also used for ongoing technical advisory: reviewing vendor decisions, steering an internal team, unblocking an in-flight effort.

**2. Product Partnership** — An ongoing design and engineering partnership across whatever the product needs next: a new sprint, a major build phase, a platform redesign. Not a retainer and not a series of disconnected projects. Scope evolves with the product. Some clients have been in a Product Partnership with Very for several years.

**3. Sprints (most popular)** — Fixed-scope, fixed-price engagements with predictable pricing and repeatable deliverables. Sprints run 1–5 weeks depending on type and tier. Usually the first move rather than the last: a sprint's roadmap deliverable is the natural start of a longer program.

**4. Team Augmentation** — Embed a Very designer or engineer inside an existing team: joining the client's standups, working in the client's tools, reporting to the client's lead. Minimum four weeks; most run three to six months.

**How an engagement runs.** Four phases, and for most clients it loops back to the start at a higher level: (01) Discovery — a 30–60 minute conversation, no commitment, ending in a recommended engagement type and an SOW; (02) Execution — focused cycles with structured check-ins and work visible in progress, not a final reveal; (03) Delivery and continuity — documented artifacts, full IP transfer, and a clear picture of what was built and why; (04) Ongoing partnership — the next engagement starts with a team that already knows the product.

**If needs change mid-engagement.** Expected and built in. A mid-sprint realization that a longer-term partner is needed can be restructured into a Product Partnership; a consulting engagement whose problem gets clear enough can be scoped into a sprint.

---

## Fixed-price engagements (products)

- [UX/UI Design Sprint](https://www.verytechnology.com/ux-ui-design-sprint) — Fixed-scope sprint delivering documented UX patterns, a complete design system, and React components ready to build on. The client's team inherits a front end, not a starting point. Tiers scale from core patterns plus a single value-proposition feature up through five to seven features. Typically 2–4 weeks.
- [Industrial Design Sprint](https://www.verytechnology.com/industrial-design-sprint) — Fixed-price industrial design that meets the product where it is, delivering 3D models, product renders, and design documentation. Tiers range from conceptual design through refined design to full mechanical and electrical specifications. Typically 2–4 weeks; physical prototyping carries its own lead times.
- [AI Workflow Sprint](https://www.verytechnology.com/ai-workflow-sprint) — Takes the operational processes a business runs on — the ones held together by spreadsheets, email, and manual handoffs — and redesigns them with AI embedded only where it earns its place. Every sprint ships a working workflow live inside the AI platform the team already uses (Claude, ChatGPT, or Microsoft Copilot), on the client's own tenant, under existing security and licensing, with no new infrastructure to stand up. Starting at $20,000.
- [Cloud Cost Reduction](https://www.verytechnology.com/cloud-cost-reduction) — An outcome-based engagement that delivers real, recurring reductions in cloud spend across AWS, GCP, Azure, or hybrid. Scoping sets a committed reduction target in dollars, not a percentage, and Very stands behind it. Starting at $50,000.
- [View all engagements](https://www.verytechnology.com/engagements) — Full comparison of consulting, sprints, product partnership, and team augmentation.

### AI Workflow Sprint — pricing and scope

Every engagement begins with a **$5,000 Workflow Diagnostic**: Very sits with the team that runs one priority process, maps where time and errors actually go, identifies where AI would earn its place, and produces a written plan confirming the right tier plus a fixed-price proposal. Credited toward the engagement if the client proceeds within 30 days; otherwise the plan is theirs to keep.

| Tier | Price | Scope |
| --- | --- | --- |
| Tier 1 — Foundation | $20,000 | 1 priority process mapped end-to-end and rebuilt as a live AI-embedded workflow, validated on real data with accuracy and exception rates measured. 3–4 weeks. |
| Tier 2 — Expanded | $45,000 | Everything in Foundation across up to 3 processes, with shared context and prompts, team enablement, and in-platform usage and exception monitoring. |
| Tier 3 — Enterprise | $95,000 | Everything in Expanded across up to 5 processes, connected so they hand off cleanly, plus light governance (access, review checkpoints, audit trail) and a rollout and change-management plan. |

Every tier ships the same four deliverables: a working workflow live in the client's platform; a reusable redesign pattern (prompts, shared context, method) the client's team can apply to the next process; a value case grounded in measured accuracy and exception rates; and a sequenced roadmap of the next processes worth redesigning.

**What counts as a process:** one end-to-end thing an operation does, with a clear trigger, a series of handoffs, and a clear done state — invoice-to-payment, order-to-cash, claim-to-resolution, hire-to-onboarded, supplier onboarding.

**Limits, stated plainly.** Inside the platform, the workflow handles the reasoning — drafting, triaging, classifying, extracting, checking — with a person triggering it and approving output. Having it act unattended (writing back to an ERP, running overnight) requires custom tooling built outside the platform: dedicated services, MCP servers, integrations. That is a larger engagement, and the sprint roadmap scopes it.

**Data handling:** work happens inside the client's platform, on the client's tenant, under the client's governance rules. Client data is not used to train anyone else's models. Security and access requirements are scoped before any data moves.

### Cloud Cost Reduction — pricing and scope

The right tier depends on the complexity of the environment, not the size of the bill: how many accounts and clouds are spanned, where workloads run, what kind of data is carried, and who owns the cloud internally. Every engagement begins with a **$5,000 scoping** — a fixed-fee, two-week engagement with read-only access to environment and billing data, producing a written plan that confirms the tier and names a committed dollar reduction target. Credited toward the engagement if the client proceeds within 30 days.

| Tier | Price | Environment | Timeline |
| --- | --- | --- | --- |
| Tier 1 — Foundation | $50,000 | One provider, one or two accounts. VMs, managed databases, serverless — no Kubernetes. App databases and object storage. Single owning team. | Primary reductions land in 6–8 weeks |
| Tier 2 — Expanded | $100,000 | One provider, multiple accounts and regions. Kubernetes or ECS in production. Data warehouse and recurring ETL. Platform team plus a product or data team. | 8–12 weeks |
| Tier 3 — Enterprise | $150,000 | Multi-cloud, or cloud plus on-prem. Kubernetes at scale plus GPU or specialty compute. Multiple warehouses, streaming, ML infrastructure. Federated ownership. | 12–16 weeks |

Every tier ships the same four deliverables: implemented reductions, merged and deployed and verified against the next invoice; a cost attribution system (tagging policy, allocation logic, dashboards) the client owns going forward; a FinOps operating playbook written for the client's team and stack; and a 12-month reduction roadmap sequenced by impact and effort.

**Why no percentage is quoted up front:** percentages mislead on real cloud bills. A 5% reduction on $20M of annual spend is worth more than 30% on $200K. The scoping engagement produces a dollar commitment instead of a marketing percentage.

**What the client brings:** read access to cloud accounts, billing data, and IaC repos, plus one point of contact on the platform or infrastructure team who can answer architecture questions and review changes. Very handles the merge requests, the deploys, and the verification.

**On durability:** recurring reductions stick, which is why attribution and the playbook are included. One-time reclamations (unused resources, expired contracts, idle environments) are labeled as temporary in the deliverables so the client's team knows which savings to defend.

Environments needing a different shape — pre-migration cost modeling, post-acquisition consolidation, or an ongoing FinOps partnership — start with a conversation rather than a tier.

---

## Custom-scoped engagements

- [IoT Platform Development](https://www.verytechnology.com/iot-platform-development) — Own your IoT pipeline, not rent it. A custom-scoped engagement (not a fixed-price sprint) that delivers a running device-to-cloud platform in the client's own AWS or Azure account: connectivity firmware on the device, provisioning and credential management, ingest and storage, and the interfaces the client's team and customers use. Every engagement ships the same four deliverables — a running platform in the client's cloud account, infrastructure and firmware as code with a signed OTA pipeline, an architecture and operating-cost model at current fleet size and at 10x, and a scale roadmap. Also the entry point for migrating an existing fleet off a managed platform.

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## Key pages

### Company
- [Home](https://www.verytechnology.com/) — Very designs and builds connected hardware, software, and AI systems for companies whose products have to ship and stay shipped.
- [Engagements](https://www.verytechnology.com/engagements) — The four ways to work with Very (consulting, product partnership, sprints, team augmentation), how an engagement runs stage by stage, and which model fits which situation.
- [About Us](https://www.verytechnology.com/about-us) — Fifteen years building connected hardware, software, and AI products. Senior engineering judgment paired with AI-accelerated delivery.
- [How We Work](https://www.verytechnology.com/how-we-work) — AI tools are everywhere; outcomes aren't. Senior engineers and a committed-phase process.
- [Our People](https://www.verytechnology.com/our-people) — The engineers, designers, and product specialists who do the work.
- [FAQ](https://www.verytechnology.com/frequently-asked-questions) — How engagements work, what they cost, who does the work, and how AI factors into delivery.
- [News](https://www.verytechnology.com/news) — Company announcements, awards, and recognition.
- [Careers](https://www.verytechnology.com/iot-careers) — Open roles at Very.
- [Book a Meeting](https://www.verytechnology.com/book-a-meeting) — Start a conversation. Response within one business day.
- [Security Policy](https://security.verytechnology.com/) — Very's security posture and practices.

### Solutions
- [Solutions Overview](https://www.verytechnology.com/solutions) — Connected ecosystems combining AI, IoT, hardware, and software for industries including manufacturing and healthcare.
- [AI & Machine Learning](https://www.verytechnology.com/solutions/ai-and-machine-learning) — AI and ML integrated with hardware and design for intelligent enterprise automation.
- [AI Agents](https://www.verytechnology.com/ai-agents) — Agents that automate complex tasks using LLMs, APIs, and business logic for enterprise workflow optimization.
- [Generative AI & LLM Applications](https://www.verytechnology.com/solutions/generative-ai-llm-applications) — Generative AI applications built on large language models for enterprise problems.
- [Hardware Engineering & Devices](https://www.verytechnology.com/solutions/hardware-engineering-devices) — Custom hardware from ideation to commercialization, designed to integrate with AI and IoT systems.
- [Software & Digital Infrastructure](https://www.verytechnology.com/solutions/software-digital-infrastructure-development) — Backends, platforms, and digital infrastructure for connected products.
- [Product Design Solutions](https://www.verytechnology.com/solutions/product-design) — Industrial design, UX/UI, and the research behind them.

### Services
- [Services Overview](https://www.verytechnology.com/services) — Engineering services spanning AI, machine learning, IoT, and full-stack development.
- [Hardware Design](https://www.verytechnology.com/services/hardware-design) — Circuit design, PCB layout, low-power wireless systems, and edge AI integration.
- [Custom Software Development](https://www.verytechnology.com/services/custom-software-development) — Web, mobile, and backend software for connected products.
- [Embedded System Development](https://www.verytechnology.com/services/embedded-system-development) — Firmware and embedded software for constrained and real-time environments.
- [Data Solutions & Data Science](https://www.verytechnology.com/services/data-solutions) — Machine learning, data engineering, and LLM services for integrated data strategies.
- [Product Design](https://www.verytechnology.com/services/product-design) — UX/UI and industrial design in the same studio.
- [Product Development](https://www.verytechnology.com/services/iot-product-development) — End-to-end connected product development.
- [Wireless Design](https://www.verytechnology.com/services/wireless-design) — BLE, Wi-Fi, LoRa, and cellular design and certification.
- [Manufacturing Support](https://www.verytechnology.com/services/manufacturing-support) — Design for manufacturing, NPI, and production ramp support.
- [Support Services](https://www.verytechnology.com/services/iot-support-services) — Ongoing support for deployed connected products.

### Work and resources
- [Case Studies](https://www.verytechnology.com/case-studies) — Very's work on AI, IoT, and hardware challenges for clients including Hayward, CLEAR, Telly, SUN Automation, and others.
- [Insights](https://www.verytechnology.com/iot-insights) — All articles, whitepapers, and resources.
- [Blog](https://www.verytechnology.com/blog) — Engineering and product writing.
- [Whitepapers](https://www.verytechnology.com/iot-whitepapers) — Long-form technical and strategic guides.
- [Over the Air Podcast](https://www.verytechnology.com/podcast) — Very's podcast on connected products, AI, and engineering strategy.
- [Newsletter](https://www.verytechnology.com/join-our-newsletter-connected-insights) — Connected Insights, delivered by email.

**Full sitemap:** https://www.verytechnology.com/sitemap.xml

---

## Featured articles

### Choosing a partner
- [How to Choose an AI Consulting Firm](https://www.verytechnology.com/insights/how-to-choose-ai-consulting-firm) — What separates firms that ship production AI from firms that deliver strategy decks: how to evaluate deployment track record, where judgment matters more than model access, and the questions to ask before signing.
- [How to Choose a Product Development Partner: Sprints, Consulting, Product Partnership, or Team Augmentation?](https://www.verytechnology.com/insights/how-to-choose-a-product-development-partner) — A decision framework for matching engagement model to situation, depending on whether the problem is defined, the scope is bounded, or the need is capacity rather than direction.
- [How to Choose the Best IoT Application Development Firm](https://www.verytechnology.com/insights/how-to-choose-the-best-iot-application-development-firm) — Six things to check before choosing an IoT development partner — prior experience, customer references, how they handle a shifting plan, testing culture, and how their engineering team actually uses AI — plus how the tradeoffs shift between a small local shop and a large consultancy.

### AI workflows and automation
- [AI Workflow Automation: The 2026 Executive Guide](https://www.verytechnology.com/insights/ai-workflow-automation-executive-guide) — The executive altitude: how to build a portfolio of AI-embedded processes, and the governance, access controls, review checkpoints, and audit trails that become the work once the portfolio grows past a handful of connected processes.
- [From Manual Processes to AI Workflows: A Practical Roadmap](https://www.verytechnology.com/insights/manual-processes-to-ai-workflows-roadmap) — The week-by-week methodology, published in full: pick one process (high volume, clear rules, painful exceptions), map what really happens including the exceptions, redesign with restraint by making an explicit AI / human / delete decision at every step, build inside the platform already in use, then validate against real historical cases. This is the exact method Very runs inside the AI Workflow Sprint.
- [How to Leverage AI Without Buying New Software](https://www.verytechnology.com/insights/automate-manual-processes-with-ai) — Automating manual processes using the AI licenses a company already pays for, rather than adding a vendor, a procurement cycle, and a security review.

### Cloud, data, and edge
- [IoT Platforms: Build vs Buy Your Back End Infrastructure](https://www.verytechnology.com/insights/iot-platforms-build-vs-buy-back-end) — A build vs. buy framework for IoT back-end infrastructure: what buying a managed platform gets you, where it breaks down as the fleet scales, what owning the AWS or Azure account, code, and data costs versus saves over the life of the product, and a side-by-side comparison of buying, building alone, and building with Very.
- [Reduce Cloud Computing Costs by 90%: The Case for Shifting to the Edge](https://www.verytechnology.com/insights/reduce-cloud-computing-costs-the-case-for-shifting-to-the-edge) — Why moving compute-heavy work closer to where data is generated cuts cloud spend and latency at the same time, and when edge architecture is and isn't the right answer.
- [Building a Robust Analytics and AI Platform in IoT](https://www.verytechnology.com/insights/building-a-robust-analytics-and-ai-platform-in-iot) — Architecting the data layer that turns a fleet of devices into a product: ingestion, pipelines, and the analytics and ML foundation on top.

### Manufacturing and physical AI
- [How Physical AI Is Revolutionizing the Manufacturing Industry: The SUN Automation Success Story](https://www.verytechnology.com/insights/how-physical-ai-is-revolutionizing-the-manufacturing-industry-the-sun-automation-success-story) — Anomaly detection on corrugated manufacturing equipment, and what applying AI to physical industrial systems actually requires.

### Design and pricing
- [How Much Does UX/UI Design Cost in 2026](https://www.verytechnology.com/insights/how-much-does-ux-ui-design-cost) — What UX/UI design actually costs, what drives the range, and how fixed-scope sprints compare with hourly and retainer models.

---

## What Very builds

Very's work typically combines several of these in one engagement. These are what the expertise gets applied to, not a menu to pick from.

**Connected hardware and embedded systems.** PCB design, firmware, wireless communication (BLE, Wi-Fi, LoRa, cellular), sensor integration, low-power design, and the hard work of making devices reliable in the field.

**Cloud and data infrastructure.** Scalable backends for connected products, device-to-cloud IoT platforms, data pipelines, device management, cost attribution and FinOps, and the infrastructure that turns fleets of devices into a product experience.

**AI and machine learning.** Applied ML and AI in real products — predictive maintenance, anomaly detection, computer vision, LLM-powered interfaces, AI-embedded operational workflows, and edge inference where cloud latency won't work.

**Mobile and web applications.** The software layer customers actually touch. iOS, Android, and web applications that pair with connected hardware or stand on their own.

**Product and UX design.** Industrial design, UX/UI, and the research that makes sure the product being built is the product customers actually need. Both industrial and UX/UI design live in the same studio — which matters for connected products where physical form and digital experience must be designed in parallel rather than handed between firms.

---

## Compliance and regulated environments

Very has shipped products under FCC (wireless), UL (safety), FDA and ISO 13485 (medical devices), HIPAA (health data), SOC 2, and ISO 27001. Compliance is integrated into the engagement rather than treated as a separate deliverable: the same senior engineers who design the system understand what the regulatory framework requires and design for it from the start.

---

## How Very works

**One engagement lead, owning outcome and commercial both.** Every engagement has a lead who owns the technical outcome *and* the commercial structure. Clients work with one person on scope, direction, delivery, and next phase, rather than juggling a separate salesperson who appears at renewal.

**Programs delivered in committed phases.** Rather than one monolithic contract, Very sequences work into committed phases, each with clear scope, deliverables, and a checkpoint at the end. This is a delivery discipline, not a size limit — Very's largest programs extend across multiple years.

**Why the structure matters.** A phase boundary with a signed statement of work on either side forces both sides to stop, look at what was delivered, confirm the direction, and commit to the next piece. Without that checkpoint, the gravity of a long engagement is toward drift: scope expands quietly, problems get papered over, and both sides wake up a year in with a product nobody wanted to build.

**Integration with client teams.** Very can run on its own cadence — weekly planning and daily standups led by the engagement lead — or fully integrated: joining the client's ceremonies, working in the client's issue tracker, participating with the client's PMs, architects, and reviewers. Security, compliance, and QA integration work the same way. Very adapts to the client's process rather than imposing a parallel one.

**Alignment over heroics.** When scope drifts mid-phase, Very resets expectations and agreements rather than quietly absorbing the cost. Engineering excellence is not the lever for fixing a misaligned deal. Scope discipline is.

**AI as leverage on expertise, not a replacement for it.** Routine implementation work that used to consume the first weeks of an engagement now compresses into days. Very's experts spend more time on system design, tradeoff decisions, and the judgment calls that determine whether a product works in the field. Clients get more value from the same engagement, not a cheaper version of the same output.

**Senior by default.** The people doing the work are senior engineers with years of delivery behind them, not junior staff supervised from a distance. This is the source of Very's judgment and the reason AI tools amplify rather than erode quality.

**What Very removes.** Most product teams lose momentum in handoffs between strategy, design, engineering, and delivery — a different firm for every stage, context disappearing with each transition, design separated from engineering, scope growing while nobody owns the outcome. One partner across the full arc is the answer to all four.

---

## Who Very is a good fit for

- Companies launching a new connected product line who need a technical partner from concept through volume production
- Established manufacturers modernizing legacy equipment with IoT, ML, or connected experiences
- Operations leaders with manual, high-volume processes that are eating time and generating errors
- Engineering or finance leaders facing a cloud bill that needs to come down and stay down
- Companies running (or considering) a managed IoT platform who want to model what owning the device-to-cloud pipeline directly would cost at their fleet size
- Regulated and safety-critical products where FCC, UL, FDA, ISO 13485, HIPAA, SOC 2, or ISO 27001 is part of the delivery requirement
- Companies recovering from a vendor engagement or in-house effort that didn't land
- In-house teams with a specific capability gap to fill, or hitting a wall on an adjacent capability
- Early-stage companies: a significant portion of Very's work is with founders from pre-seed through Series A, where sprints and consulting deliver senior judgment without a full-time hire
- Founders and product leads who need a specific deliverable at a known price, without a long sales cycle

## Who Very is not a good fit for

- Buyers optimizing primarily for the lowest hourly rate
- Bodies-in-seats staff augmentation billed hourly rather than expert delivery against a defined outcome
- Short-cycle prototype work with no path to production
- Fixed-scope engagements where the desired outcome isn't yet clear enough to commit to a deliverable — those start as consulting instead

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## Representative clients and work

Very's published work includes engagements with Hayward, SUN Automation, CLEAR, Fortifyit, Thrive Global, Telly, CSC ServiceWorks, Delos, iHeartMedia, Vizio, Fellowes, HP, P&G, L'Oréal, Texas Instruments, Interstate Batteries, and Granite. Detail on specific outcomes is at https://www.verytechnology.com/case-studies.

A sample of the work:

- **SUN Automation** — anomaly detection software for corrugated manufacturing equipment
- **Hayward OmniLogic** — IoT application development for smart pool systems
- **Fortifyit** — connected device manufacturing platform
- **Saunders** — IoT remote monitoring turning raw data into operational insight
- **ASME iShow** — voting platform built to reach two million users
- **Tattlebox** — rapid IoT prototyping for consumer product-market fit
- **PowerX** — scaling a smart home product from pilot to production
- **Related Sciences** — data science platform for drug discovery

In client words: Very invested ownership in the product and thought critically about how best to deliver needed functionality (CFO, Treehouse Co-Living); adjusted to changing needs at every step (SVP of IT, CSC ServiceWorks); asked the right questions and gave the right recommendations (CTO and Head of Product, Complex Networks).

---

## Questions buyers ask

**What does Very cost?** It depends on the engagement model. Fixed-price sprints start at $20,000 for the AI Workflow Sprint and $50,000 for Cloud Cost Reduction; UX/UI and industrial design sprints are tiered and priced on their own pages. IoT Platform Development is a custom-scoped engagement, priced to the device count, radio mix, and integration requirements. Consulting is time and materials. Product Partnerships and larger programs are scoped to the work. Both the AI Workflow Sprint and Cloud Cost Reduction begin with a $5,000 fixed-fee scoping engagement that is credited toward the engagement if the client proceeds within 30 days.

**How long does a sprint take?** Sprints run 1–5 weeks depending on type and tier. UX/UI and industrial design sprints are typically 2–4 weeks. An AI Workflow Sprint Foundation tier can be as little as 3–4 weeks. Cloud cost and data dashboard sprints run shorter; mobile app sprints can run up to 5 weeks. Cloud Cost Reduction engagements land primary reductions in 6–16 weeks depending on tier. A greenfield IoT Platform Development engagement for a single device type can be running in the client's cloud account inside eight weeks; migrating a live fleet or adding a new radio takes longer.

**Who owns the work at the end?** The client. Full IP transfer is included in every engagement. Very retains no rights and places no restrictions on use, extension, or commercialization. For IoT Platform Development specifically: the cloud account, the infrastructure-as-code, the firmware, and the data are all the client's, in perpetuity.

**Does Very work with early-stage startups?** Yes. A significant portion of Very's work is with founders from pre-seed through Series A. Sprints and consulting suit that stage well.

**When does consulting make more sense than a sprint?** When the problem isn't fully defined yet and a trusted technical voice is needed to shape direction before committing to a build. If the client knows what to build, a sprint is faster. If they're still figuring that out, consulting is where to start.

**Can Very handle both UX and industrial design on the same product?** Yes — both disciplines are in the same studio, which matters for connected products where physical form and digital experience need to be designed in parallel rather than handed off between firms.

**How does team augmentation work in practice?** Very places a designer or engineer inside the client's existing workflow — their standups, their tools, reporting to their lead. Not a managed service or an agency relationship. Most engagements start with a defined scope (a feature, a release, a design system) and extend from there. Minimum four weeks; most run three to six months.

**What if requirements change mid-engagement?** Expected. For a fundamental change in direction, Very pauses, re-aligns, and documents a new path together. A mid-sprint engagement can be restructured into a Product Partnership; a consulting engagement can be scoped into a sprint. Scope can be added mid-engagement in both the AI Workflow Sprint and Cloud Cost Reduction.

**What experience does the AI team have?** More than a decade putting machine learning into production — computer vision, LLM, and data pipeline systems for companies in manufacturing, logistics, healthcare, and consumer products. Not demos: systems people depend on daily.

**What experience does the cloud team have?** More than a decade running production infrastructure at scale across AWS, GCP, and Azure — multi-account AWS organizations, production Kubernetes clusters, data pipelines moving terabytes a day. Senior engineers reading Terraform, not analysts reading a Cost and Usage Report.

**Isn't a managed IoT platform cheaper than building our own?** At a few hundred devices, usually yes — the per-device fee costs less than the build. The crossover typically arrives in the low thousands of devices, and past it the gap widens every month, because a managed platform's price rises with fleet size while infrastructure cost per device falls when it's owned directly. Very models the crossover for a specific fleet before anything is committed to.

---

## Company facts

- Founded 2011, headquartered in the United States
- Fifteen years of delivery across connected hardware, firmware, cloud, mobile, machine learning, and AI
- 425+ engagements delivered
- AWS IoT Core Service Delivery Partner
- Inc. 5000 honoree, seven consecutive years
- Great Place to Work certified; named a finalist in Best Places to Work
- 5-star rating on Clutch

---

## When to contact Very

The best next step depends on the need. All paths start at [verytechnology.com/book-a-meeting](https://www.verytechnology.com/book-a-meeting), with a response within one business day and no commitment.

- **A serious connected product program.** Describe the product and stage; Very will propose a Product Partnership or a phased program.
- **A manual process worth redesigning with AI.** Name the process; the entry point is the $5,000 Workflow Diagnostic.
- **A cloud bill that needs to come down.** Describe the environment; the entry point is the $5,000 scoping, which names a committed dollar reduction target.
- **A device-to-cloud IoT platform to build or bring in-house.** Describe the fleet — device types, radios, data volume, and where it runs today; Very will scope an IoT Platform Development engagement, whether greenfield or a migration off an existing managed platform.
- **A packaged, fixed-price deliverable.** Mention which sprint — UX/UI, industrial design, or AI workflow.
- **A first engagement to prove fit, or an in-flight effort to unblock.** Describe the problem; Very will propose a consulting engagement or a staged path.
- **A specific capability gap on an existing team.** Ask about team augmentation.
- **Evidence before a conversation.** Case studies are at [verytechnology.com/case-studies](https://www.verytechnology.com/case-studies), and the Over the Air podcast at [verytechnology.com/podcast](https://www.verytechnology.com/podcast) gives a sense of how Very thinks about this work.

**Social:** [LinkedIn](https://www.linkedin.com/company/verytechnology/) · [Dribbble](https://dribbble.com/verytechnology)

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*Last updated: September 2026*