AI Feature Sprint — Ship a production AI feature in 4 weeks
Deliver real, application-level AI your users feel inside your product—not a lab demo. In one month, we design, build, and launch a single high-impact feature (e.g., knowledge assistant/RAG, customer support copilot, document & case intake/IDP, decision & approval automationwith agentic workflows, recommendations/pricing, or real-time voice). You get security and governance from day one, plus clear KPI measurement.
What to expect
ISO/IEC 27001 & 9001, model-agnostic (AWS Bedrock, OpenAI, Azure, Gemini), EU & US delivery, data privacy by design
Who this AI sprint is for
- Teams that want business outcomes fast—not another PoC
- Product/ops leaders with a clear process pain (slow intake, long handling times, inconsistent answers).
- Orgs that need a governed path to launch: privacy, access control, audit, and predictable costs.
- Companies seeking AI consulting & integration with their existing stack, without a re-platform.
What you get
A shipped feature
A shipped feature inside your app (copilot, IDP, RAG, agentic workflow, recommendations, or voice).Assistive UX
Assistive UX that users understand (clear states, explanations/citations, approvals).Security & governance plan
Least-privilege access, audit logs, human-in-the-loop where needed.Cost guardrails
Unit economics, prompt caching, routing tiers, and budgets.Extended support
Run-book & training for operations, plus a 90-day improvement plan.
The 4-week AI power plan
Week 1 — Discover & Design
We start from your process and KPI. Together we pick one high-leverage use case and design exactly where the AI lives in your UI and what "good" looks like.- Map user journey and success metrics
- Define data/permissions and guardrails
- Agree the minimal lovable release (MLR)
Week 2–3 — Build & Integrate
We build the feature, connect it to your systems and content, and ensure model-agnostic flexibility.- Implement application-level AI pattern (RAG, IDP, agentic workflow, recommendations, or voice)
- Integrate with your APIs/tools; add approvals/logging
- Prepare adoption enablement (help, tips, metrics)
Week 4 — Harden & Launch
We make it production-ready, measurable, and safe.- Add evaluation (quality/faithfulness/safety/latency) & alerting
- Set cost guardrails and usage budgets
- Launch to a pilot cohort; finalize the run-book
Popular sprint use cases
Knowledge assistant for teams (RAG)
Ask in plain language; get answers with citations from policies, wiki pages, tickets, and docs. Impact: less search time, fewer escalations, faster onboarding.Customer support copilot (chat/voice)
Drafts replies, proposes safe actions, executes with approval. Impact: higher first-contact resolution, better CSAT, lower handle time.Document & case intake (IDP)
Classify → extract → validate → post invoices, POs, claims, contracts. Impact: less manual entry, fewer errors, audit-ready trails.Decision & approval automation (agentic workflows)
Agents gather evidence, check rules, and propose decisions for human sign-off. Impact: shorter turnaround, consistent compliance.Pricing, recommendations & promotions
Dynamic pricing and next-best actions with explainable controls. Impact: higher conversion and LTV, fewer returns.Voice & real-time assistants
Natural, interruptible voice to schedule, confirm, route, and update cases. Impact: faster service, fewer no-shows.
Security & data governance
Quality & security
ISO/IEC 27001 & 9001 delivery.Privacy by design
Privacy by design: PII/PHI handling, data minimization, configurable retention.Identity & access
Identity & access: SSO/SAML, least-privilege policies, agent identities, action logs.Human-in-the-loop
Human-in-the-loop: approvals where accuracy or risk demands it.Model/data controls
Model/data controls: Your data is never used to train third-party models without consent.Auditability
Auditability: end-to-end logs and exportable trails.
Cost control & model choice
Predictable unit economics
Predictable unit economics with prompt caching, routing tiers, token budgets, and usage dashboards.Model-agnostic delivery & LLM gateway
Model-agnostic delivery via an LLM gateway (Claude, GPT, Gemini—and others) so you're never locked in.Post-launch MLOps consulting
Optional MLOps consulting after launch for monitoring, regression tests, red-teaming, and drift control.
AWS Partnership & Cloud Funding Support
AWS Partnership & Cloud Funding Support
As an AWS Partner, we help eligible customers access AWS‑funded Proof‑of‑Concept (PoC) credits and other promotional funding to de‑risk AI initiatives and migrations.
We also run fast, practical assessments to align your roadmap with AWS best practices.
PoC / Pilot credits*
We identify a high‑value use case, scope the pilot, prepare the AWS request, and deliver a measured proof with a clear ROI plan.*Where applicable. Contact us for more details.Assessments
AWS Well‑Architected Review (WAR), Migration Readiness Assessment (MRA), cost‑optimization & modernization reviews, and AI readiness on AWS.GenAI on AWS
Pragmatic patterns using Amazon Bedrock and AWS‑native services—delivered with governance and cost controls.
What we need from you
- A clear process pain or opportunity (and a KPI target).
- Access to content/systems relevant to the use case (e.g., policies, tickets, docs, sandbox APIs).
- A small decision group for fast feedback and approvals.
- A plan for a pilot cohort (e.g., one team or region).
After the sprint
Operational scale-up
Scale to more users with the run-book and training we provide.Performance tuning
Monthly reviews to tune prompts/retrieval, add data sources, and optimize costs.Strategic AI expansion
Expand to the next AI software development opportunity using the same, proven path.
Insights into Generative AI development
Enterprise AI Integration Playbook (Part 3): Infrastructure, Talent & the Path from PoC to Production
Scale AI beyond prototypes with the right data strategy, cross-functional talent, and a modular stack. Compare cloud vs on-prem vs hybrid, and follow the PoC→pilot→production path with reliable MLOps.
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Balancing AI Integration Costs: Build From Scratch or Upgrade Existing Systems?
Discover detailed TCO insights for integrating AI: compare greenfield development with embedding AI into existing infrastructure. Learn cost drivers, ROI, and when each approach makes financial sense.
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Cloud vs. On‑Premise Infrastructure: Comparison Guide for IT Leaders
Cloud adoption soars, yet on-premise remains vital for control, cost, and compliance. This guide weighs CapEx vs OpEx, latency, security, DR, and hybrid models to help IT leaders choose wisely.
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FAQs
Is 4 weeks realistic?
Yes—by focusing on one valuable, well-scoped feature. We prioritize business impact over breadth.Do you provide AI consulting and AI software development?
Yes. We combine AI consulting services (use-case discovery, ROI, governance) with AI software development services and AI integration services to ship real features.Which models and platforms do you support?
We’re model-agnostic and work across AWS Bedrock, OpenAI, Azure, and Gemini—choosing the best fit and keeping swap-ability.How do you protect our data?
ISO-aligned processes, least-privilege access, audit logs, and human-in-the-loop where needed. Your data is not used to train third-party models without consent.How do we measure success?
We agree KPIs up front (e.g., handling time, FCR, cycle time, conversion) and launch with baselines, evaluation, and dashboards.
Let’s ship one valuable AI feature-fast
Contact us and get your project moving
Describe your needs to us and we'll work together to craft the perfect software solution. Tell us your timeframes, your targets or KPIs, and any critical challenges or difficulties. You're at the right place — our team is eager to study and prioritize next steps together with you.Have a project in mind?