BrainOS is an AI consultancy built by people who've shipped AI products inside Microsoft, Adobe, and other scale companies. We don't just advise — we build, integrate, and operate AI systems that move business metrics.
Our differentiator is BrainOS: a proprietary execution framework and agentic tooling that compresses timelines and cuts the gap between pilot and production.
Each engagement is scoped to your organization's readiness, goals, and where you'll get the most leverage first.
Assessment of where AI creates the most value in your organization — mapped against your workflows, team capabilities, and existing tech stack. Delivered as a prioritized roadmap with clear sequencing and resource estimates.
Equipping your teams to work with AI as a daily practice — not a one-time training. We build internal capability that outlasts any engagement, through process design, tooling choices, and hands-on coaching.
Building AI agents and automations that operate inside your existing stack — handling workflows, decisions, and data flows at scale. Leveraging BrainOS tooling to accelerate development.
Getting your AI use compliant, auditable, and defensible — for internal deployments, vendor evaluations, or regulatory requirements. Covers frameworks, documentation, and controls.
When your problem doesn't fit a standard mold — or when you need senior-level execution on a specific initiative. We scope bespoke engagements for complex, high-stakes AI work.
Most organizations have no shortage of AI ideas — they have a shortage of clarity about where AI creates real business value versus where it creates busywork. We start by mapping your workflows, team capabilities, and existing tech stack against a prioritized use-case matrix so you know exactly where to invest first.
Good AI strategy isn't about adopting AI for its own sake. It's about identifying the three or four places where AI can move a business metric — and sequencing the work so you're building momentum, not scattered experiments.
Deliverables include an organizational AI readiness audit, a build-vs-buy-vs-integrate framework for each opportunity, and a phased roadmap with resource estimates and risk considerations.
Technology without capability is just expensive software. We equip your teams to work with AI as a daily practice — not a one-time training exercise that fades. The goal is internal muscle that outlasts any engagement.
That means designing workflows around how your teams actually work, selecting and configuring tools that fit your stack, building prompt libraries and best practices specific to your domain, and running change management programs that get genuine adoption — not just reluctant sign-off.
Success looks like: your team running AI-enhanced workflows without needing to call anyone. Your processes designed to learn and improve over time. Your tooling decisions grounded in actual usage patterns, not vendor marketing.
Agents are AI systems that do work — not just generate outputs, but operate inside your existing stack, handling workflows, decisions, and data flows at scale. We design and build custom agents for your specific context, leveraging BrainOS tooling to accelerate development and ensure production-grade reliability.
The difference between a useful AI tool and a production AI agent is the difference between a prototype and a system your business depends on. We build to that standard: monitoring, observability, error handling, and iteration loops built in from day one.
Deliverables include custom AI agent design and build, workflow automation orchestration, integrations with your existing tools and data sources, and monitoring dashboards so you can see what the agent is doing.
AI deployments are increasingly subject to regulatory scrutiny, internal audit requirements, and vendor due diligence. Getting ahead of this isn't just about compliance — it's about building AI systems you can defend to regulators, customers, and your own board.
We design governance frameworks that work for your specific risk profile: startups moving fast don't need enterprise compliance theater, but enterprises with customer data responsibilities need real controls. We meet you where you are and build what's actually needed.
Deliverables include AI governance framework design, policy and documentation for compliance, vendor and tool evaluation against your requirements, and audit readiness assessment with gap remediation.
Some problems don't fit a standard mold — or they require senior-level execution on a specific initiative where the stakes don't allow for learning on the job. We scope bespoke engagements for complex, high-stakes AI work.
This might be executive-level advisory for a company making its first major AI investment. A complex integration where the technical risk is high and the cost of failure is real. M&A due diligence on AI assets where you need people who've built these systems, not just studied them. Board and investor readiness for companies whose AI story is part of their valuation narrative.
We scope these engagements directly with principals — no junior staff, no discovery phases that bill by the hour while you wait for insight. You get senior attention from people who've done this before.
We work with companies that have moved past the "should we use AI?" question and are focused on "how do we actually make it work?"
Companies with product teams that need AI features shipped faster and more reliably than internal capacity allows.
Firms where knowledge work is the product — looking to augment teams with AI without replacing client relationships.
Organizations with complex internal processes — supply chain, finance, HR, customer service — where AI can compress costs and reduce friction at scale.
Founders building AI-native products or embedding AI capabilities as a core differentiator — who need a partner that can execute at startup speed.
Most AI consultancies start from scratch on every engagement. BrainOS is our proprietary execution framework — built from years of shipping AI products at scale — that gives us a head start on every problem we take on.
Reusable AI agent architectures for common workflows — adapted to your stack, not built from scratch.
Built-in metrics, monitoring, and feedback loops so AI systems don't degrade silently.
Battle-tested patterns for connecting AI to CRMs, databases, communications tools, and custom systems.
Structured handoff methodology so your team owns the system when we're done.
What this means for you: faster timelines, lower risk, and an AI system that's built to be maintained by your team — not by us indefinitely.
Every engagement follows the same structured process — adapted to scope, timeline, and your team's readiness, but never skipped.
We map the problem space: where you're trying to get to, what constraints you have, what's been tried before, and what success looks like at a business level. Done through working sessions with your team — not a questionnaire dropped in your inbox. Takes 1–2 weeks depending on scope.
From discovery, we produce a strategy document: clear problem definition, a phased approach with sequencing, resource and timeline estimates, and risk considerations. This is the blueprint every engagement follows. We don't move to build until you agree the strategy is right.
Execution against the strategy — building AI systems, integrating with your stack, designing workflows, and getting your team ready to operate. We run in short cycles with regular check-ins, not a black-box handoff at the end. You see progress continuously, not just at the finish line.
Knowledge transfer and team enablement so the system is yours to own, operate, and improve. Documentation, training, and a structured handoff process — not a "good luck" email with a Confluence link. We stay until your team can fly without us.
We measure success by what your business can do after — not what we handed over during.
Every engagement is scoped to produce working systems — not slide decks or strategy documents that collect dust.
BrainOS tooling compresses what used to take 6 months into 6 weeks. You see working AI sooner, with less risk.
We build your team's ability to own, operate, and improve AI systems — not a dependency on us for maintenance.
AI systems connected to your KPIs — so you can see the actual ROI, not just the technology working in isolation.
Results below are from anonymized client engagements. Identifiers are intentionally generic; ranges are reported from a single representative engagement per vertical.
Most engagements are scoped as fixed-price projects — we define the problem, agree on scope, and deliver for a set investment. This works well for defined problems with clear deliverables. For on-going advisory or larger multi-phase engagements, we use a retainer structure with monthly scope. We don't bill by the hour — our incentive is to solve your problem efficiently, not extend the engagement.
It depends on scope. A focused AI strategy engagement can be 4–6 weeks. A full agentic system build typically runs 8–16 weeks. Custom engagements vary by definition. The common thread: BrainOS tooling lets us move significantly faster than typical consultancy timelines — what might take 6 months elsewhere often takes 6 weeks with us.
We typically work with engagements starting at $15k. For smaller, well-defined problems we can sometimes point you to simpler solutions that don't need our involvement. We won't take an engagement unless we're confident we can deliver meaningful results — if the scope doesn't justify working with us, we'll tell you.
Every engagement includes a formal transfer phase where we make sure your team can own, operate, and improve what we've built. Documentation, training, and a structured handoff process are included — not add-ons. After that, we offer optional retainer arrangements for ongoing advisory, but there's no lock-in. If your team can run it alone, we want them to.
Yes — when AI is a core strategic priority for you, not a nice-to-have. We work with founders building AI-native products, embedding AI capabilities as a core differentiator, or preparing for a fundraise where AI story is part of the narrative. For these engagements, we move fast and stay scrappy — the BrainOS framework is built for startup velocity.
We work with your data security requirements, not around them. For sensitive data, we can operate within your cloud environment, use isolated processing, and provide documentation for compliance audits. We don't use client data to train models. Every engagement starts with a security and privacy review as part of discovery — if there are requirements we can't meet, we tell you upfront.
If you're early in the process — not sure what you need, whether AI is the right lever, or what an engagement might look like — book a call. No pitch, no discovery questionnaire. Just a direct conversation about where you're at and what might help.
Tell us about your situation — where you're at, what you're trying to achieve, and what stood in the way last time. We'll respond within one business day.