AI Agent Development Services Production-Ready Agents in 4 Weeks
Our AI agent development services deliver production-ready agents copilots, document processors, knowledge assistants, workflow agents embedded directly in your product flows.
In one month, we define, build, and launch a single high-impact agent tied to your business KPIs. Production-ready from day one, with governance, security, and measurement included.
What to expect
ISO/IEC 27001 & 9001, model-agnostic (AWS Bedrock, OpenAI, Azure, Gemini), EU & US delivery, data privacy by design
Who the Agent Sprint is for
- Business outcomes fast
not another pilot. - Product and ops leaders with a clear process pain (slow intake, long handling times, inconsistent answers).
- A governed path to launch: privacy, access control, audit trails, and predictable costs.
- Agent deployment that integrates with your existing stack without a re-platform.
What Our AI Agent Development Services Include
A deployed agent
A deployed agent inside your app (copilot, document processor, knowledge assistant, workflow agent, or voice agent).Embedded UX
Agent embedded in your product UX clear states, explanations, citations, and approval flows that users understand.Governance controls
Least-privilege access, audit trails, human-in-the-loop where needed, and strict data controls.Cost tracking
Unit economics, prompt caching, routing tiers, usage budgets, and cost monitoring dashboards.Runbook & training
Operational runbook for your team, plus a 90-day improvement plan.
Our AI Agent Development Process
Week 1 // Define the agent
Pick one high-leverage use case. We define the agent's goals, tools, data sources, and success metrics tied directly to a business KPI.Week 2–3 // Build & integrate
We build the agent, integrate it with your systems, and embed it in your product UX. Framework-agnostic: we use what works for your needs.Week 4 // Harden & deploy
We add evaluation suites, safety guardrails, human-in-the-loop controls, and observability. You launch with a production-ready agent and clear measurement.
AI Agent Development Use Cases
Knowledge agents (RAG)
Agents that surface answers from your private content with citations and reasoning grounded in policies, procedures, and documentation. Impact: less search time, fewer escalations, faster onboarding.Customer support agents
Context-aware agents that draft replies, propose safe actions, and execute with approval. Impact: higher first-contact resolution, better CSAT, lower handle time.Document processing agents
Agents that classify, extract, validate, and route data from invoices, claims, contracts, and KYC documents with human review when confidence is low. Impact: faster cycle times, fewer errors, clearer auditability.Workflow agents
Agents that gather evidence, check rules, and propose decisions for human sign-off. Impact: shorter turnaround, consistent compliance.Recommendation agents
Agents that suggest next best actions with transparent logic improving conversion and retention without friction. Impact: higher conversion and LTV, fewer returns.Voice & conversational agents
Natural, low-latency agents for voice and chat interruptible, context-aware, and integrated with your systems. Impact: faster service, fewer no-shows.
Security & data governance
Quality & security
ISO/IEC 27001 & 9001 delivery.Privacy by design
PII/PHI handling, data minimization, configurable retention.Identity & access
Agent identities, least-privilege access, action logs.Human-in-the-loop
Approvals where accuracy or risk demands it.Model/data controls
Your data is never used to train third-party models without consent.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 Agent Sprint
Operational scale-up
Scale the agent to more users and use cases using the runbook and training we provide.Performance tuning
Tune prompts, retrieval, add data sources, and optimize costs.Strategic agent expansion
Build additional agents using the same proven methodology from single agents to multi-agent orchestration.
Insights into Generative AI development
Agentic AI in insurance: beyond the chatbot
Most insurance AI projects never escape pilot purgatory. Learn why chatbots hit their ceiling and the architecture patterns for production AI agent deployment.
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The Hidden Costs of AI Agent Development: A Complete TCO Guide for 2026
Your AI agent budget is probably 40-60% too low. From infrastructure to pilot purgatory, here’s the complete TCO picture every decision-maker needs before signing a contract.
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Why 88% of AI Agents Never Make It to Production (And How to Be the 12%)
The demos impress. The pilots look promising. Then nothing happens. Discover why most AI projects die in pilot purgatory and what the successful 12% do differently.
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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.
Ready to deploy your first agent?
Tell us about your use case, your KPIs, and your timeline. We'll help you design the right agent and map out your path to production.Let's talk about your project