Your AI works in demos.
We make it work in production.
Opportune partners with Series A–D AI companies to close the gap between a working prototype and a production-grade system — without breaking.
◉ start here
Not sure where your stack is exposed?
Find out in 5 minutes.
◌ what we do
Six failure modes.
Six engineering answers.
Provider Resilience
Multi-provider routing fabrics with admission control, circuit breakers, and graceful degradation — so one provider's bad day isn't your users' problem.
Eval Infrastructure
LLM-as-judge pipelines that run pre-deploy and continuously in production. Catch regressions before users file tickets.
Retrieval Engineering
Retrieval eval pipelines, index drift detection, and purpose-built reranking. Bad retrieval is the root cause of most RAG hallucinations.
Cost Observability
Token attribution per feature, user, and team. Semantic caching and intelligent routing that typically reduces LLM bills 40–70%.
Agent Runtime Design
Agents engineered like distributed systems — idempotent operations, checkpointing, replayable traces, bounded recovery loops.
AI Incident Runbooks
Postmortems and runbooks classified by failure layer: retrieval outage, quality drift, performance, cost spike, data incident. Each with its own diagnosis tree.
Scoped, fixed-scope engagements. No open-ended retainers.
Two-week scoped review, evolving into a retainer. No retainer lock-in until you see the work.
◌ writing
Real failures.
Real postmortems.
We publish in-depth teardowns of public AI production failures — what went wrong, why, and the engineering that would have prevented it.
How Saarthi thinks in under 6,000 tokens
Context engineering · hybrid RAG · Lost-in-the-Middle mitigation
How Cursor went down 131 times in one year
Single-provider dependency · no circuit breaker · no fallback
OpenAI's 34-hour outage: an SRE postmortem
Memory limits · routing node cascade · no graceful degradation
Why 75% of CRM agent tasks fail on retry
State loss · non-idempotent operations · missing recovery paths
◌ who we are
Built by engineers
who've actually shipped.
Ramanan
Technical Lead
11 years SRE / DevOps across TikTok, WhatsApp, Amazon. PhD in Computational Linguistics, IIT Hyderabad. Deep expertise in AI infrastructure, distributed systems, and production observability.
Rohan Jahagirdar
GTM & Delivery
Deep GTM and sales background. Extensive experience in enterprise sales motions, account management, and building services delivery practices from the ground up.
◌ questions
Common questions
◌ ready to start
Find your gaps.
Then let's fix them.
The free audit takes 5 minutes. The architecture review takes 30. Either way, you'll know exactly what to fix next.