AI Strategy & Architecture Audit
AI Architecture Consulting Services to Enhance Your Applications with Powerful AI Capabilities
Our AI architecture consulting services answer the question every team should ask before building: is this the right approach, is it feasible, and what will it actually cost — before a single line of production code is written.
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The Problem With Starting Without a Map
Most AI projects that fail don't fail because of bad engineering. They fail because the team picked the wrong approach upfront — fine-tuning when RAG would have done it faster and cheaper, building a custom agent when a simpler LLM integration was sufficient, or committing to a vendor's platform before understanding the lock-in implications. These mistakes cost months and significant budget to discover. A two-week architecture audit costs a fraction of that and surfaces them before they're expensive.
What You Get Without an Audit vs. With One
Without an Architecture Audit
Approach selection: Based on what the team already knows, what's trending, or what a vendor recommended
Cost estimate: Rough guess, often significantly underestimated
Build vs. buy: Decided by preference, not analysis
Risk identification: Discovered mid-build or after launch
Team alignment: Each stakeholder has a different mental model of what's being built
With an Architecture Audit
Approach selection: Based on your specific use case, data, and constraints — RAG vs. fine-tuning vs. agents vs. prompting, with clear reasoning
Cost estimate: Scoped and documented before commitment
Build vs. buy: Analyzed against your requirements, timeline, and total cost of ownership
Risk identification: Surfaced in week one, before they cost anything to fix
Team alignment: Single documented architecture decision record everyone works from
What the Audit Covers
Use case feasibility assessment — is what you want to build actually achievable with current LLM capabilities, and what are the real constraints?
Architecture recommendation — RAG, fine-tuning, agent, prompt engineering, or a combination — with the reasoning documented, not just the conclusion
Build vs. buy analysis — for each major component, whether a vendor solution, open-source tool, or custom build is the right call given your constraints
Data readiness assessment — do you have the data you need, in the quality you need, for the approach you're considering?
Cost and timeline estimate — realistic build cost, time to production, and ongoing operational cost based on actual scope
Risk register — the top five risks specific to your use case and architecture, with mitigation options for each
AI roadmap — a phased delivery plan that gets you to a working system fastest, with clear criteria for each phase
Vendor and tooling recommendations — specific tools, models, and platforms recommended for your stack, with alternatives and trade-offs documented
Who This Is For
Teams about to commit budget to an AI build who want independent validation before signing a contract or starting a sprint
CTOs and technical leads who have a product direction but need the architecture figured out before presenting it to the board or engineering team
Companies that have already started and hit unexpected complexity — a mid-project audit to course-correct is often faster than pushing through on the wrong path
Enterprises evaluating AI vendors who need an independent technical view before committing to a platform
Trusted Across 50+ Countries
Codersarts maintains a 4.9/5 client satisfaction rating across hundreds of engagements. Clients consistently highlight clear technical communication as a differentiator — Salim (UAE) described the team's responsiveness and clarity on a complex technical engagement as the deciding factor, while Vivek (India) pointed to the team's ability to make complicated architecture decisions genuinely understandable.
Results
A Series A startup avoided a three-month fine-tuning project after an audit determined that a RAG system with prompt engineering would meet their accuracy requirements at roughly 20% of the cost and in a quarter of the time.
A mid-market SaaS company used an audit to select between three competing AI platform vendors, identifying a lock-in risk in their preferred vendor's architecture that would have constrained their roadmap within 18 months.
An enterprise IT team used a mid-project audit to course-correct an AI agent build that had stalled — the audit identified that two of the five agent tools were causing 80% of the failures, leading to a scoped rebuild that shipped in four weeks.
(Client names withheld under NDA; case studies available on request.)
Pricing
Standard Audit
Scope: Single use case — feasibility assessment, architecture recommendation, build vs. buy, cost and timeline estimate
Price: $2,000–$4,000 — delivered in 1 week
Comprehensive Audit
Scope: Multiple use cases or complex architecture — full risk register, AI roadmap, vendor evaluation, data readiness assessment
Price: $4,000–$8,000 — delivered in 2 weeks
This is the lowest-cost engagement we offer and the highest-leverage one — most clients who proceed to a build engagement start here. The audit deliverable is a standalone document you own regardless of whether you build with us.
What You Receive
Every audit delivers a single written document covering:
Executive summary (suitable for non-technical stakeholders)
Architecture decision record with full reasoning
Build vs. buy analysis per component
Cost and timeline estimate
Risk register with mitigations
Phased AI roadmap
Tooling and vendor recommendations
Delivered as a PDF and editable document. Includes a 1-hour review call to walk through findings and answer questions.
How We Work
Intake (Day 1–2) — structured questionnaire covering your use case, existing stack, data, constraints, and success criteria
Analysis (Days 3–8) — architecture assessment, research, and documentation
Review call — walk through findings, answer questions, refine any sections
Final delivery — complete audit document delivered within the agreed timeline
Why Codersarts
Our enterprise AI roadmap consulting is independent — we have no vendor relationships that bias our recommendations, and we document the reasoning behind every recommendation so you can evaluate it, not just accept it. The audit document is yours to keep and use regardless of who you build with. Most clients who build with us start here; most clients who don't build with us still tell us the audit was worth it.
Related Services
RAG Engineering & Deployment — the most common follow-on engagement after an audit recommends RAG
LLM Fine-Tuning — for audits that determine fine-tuning is the right path
AI Agent Development — for audits scoped around workflow automation and agentic systems
LLM Evaluation & Benchmark Engineering — for audits that surface an evaluation gap as the primary risk
Get Started
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FAQ
Is this just a sales pitch for your other services? No — the audit is a standalone engagement with a flat fee and a written deliverable you own. If the audit recommends a build approach that isn't in our service catalog, we'll say so. If we're not the right team to build what you need, we'll say that too.
What if we've already started building? A mid-project audit is one of our most common engagements. We assess what's been built, identify where the architecture is working and where it isn't, and produce a clear course-correction plan. It's faster and cheaper than continuing in the wrong direction.
How is this different from a free discovery call? A discovery call is 30–60 minutes and produces no deliverable. An audit is a 1–2 week structured analysis that produces a written document covering architecture, cost, risk, and roadmap — something you can present to stakeholders, use to brief a development team, or take to another vendor for a second opinion.
Do we need to share proprietary data or code for the audit? No — the audit is based on a structured questionnaire, a description of your use case and data characteristics, and your existing stack. We don't require access to proprietary data, source code, or systems.
Can the audit be used to brief a different development team if we don't build with you? Yes — it's your document. Many clients use the audit deliverable to brief internal engineering teams or other vendors. That's a feature, not a bug.